Apparatus, computer implemented method, and computer program product for improving selection and provision of operational support data objects

Abstract

Embodiments of the present disclosure provide for improved identification and output of predicted operational support data objects. Embodiments utilize implementations of particular data sets and data models to identify and select predicted operational support data objects determined to be associated with the highest degree of confidence to assist in resolving particular faults affecting network-connected devices in a dynamic home communications network. Such embodiments utilize the predicted operational support data objects to enable fault resolution with improved success rates and without requiring the execution of additional and / or alternative support processes.

Description

[Technical field]

[0001] Embodiments of the present disclosure relate generally to providing operational support data objects for faults in one or more devices, and specifically to applying device activity data and fault text description data to an operational support processing data model to select at least predicted operational support data objects for output by a client device. [Background technology]

[0002] For any of a number of reasons, a device, system, network, and / or other configuration of computing devices may experience any number of technical problems that affect its operation. Such problems may include slow performance, crashes, lack of connectivity, and the like. Users of such devices or associated with such devices will often seek resources, methods, processes, and other means to diagnose and resolve such technical problems. Applicant has discovered problems with current implementations for identifying and resolving technical problems for any number of devices, and problems with providing resources to assist in resolving such technical problems. Through applied effort, ingenuity, and innovation, Applicant has solved many of these identified problems by developing what is embodied in the present disclosure, which is described in detail below. Summary of the Invention

[0003] In general, the embodiments of the disclosure provided herein provide improved operational support data objects that address specific faults. Other implementations for providing improved operational support data objects that address specific faults will be, or become, apparent to one of ordinary skill in the art upon review of the following figures and detailed description. It is intended that all such additional implementations be included herein within the scope of this disclosure and protected by the following claims.

[0004] According to a first aspect of the present disclosure, a computer-implemented method is provided for selecting a predicted operational support data object from an operational support management repository using device activity data from a dynamic home communication network. The computer-implemented method is executable by a combination of any number of computing devices embodied in various hardware, software, firmware, and / or combinations thereof, as described herein. In one example, the exemplary computer-implemented method includes initiating a fault support session associated with a requesting client device. The exemplary computer-implemented method further includes correlating the device activity data and the fault text description data to the fault support session. The exemplary computer-implemented method further includes applying, in real time, the device activity data and the fault text description data to an operational support processing data model to select a predicted operational support data object from the operational support management repository, the operational support processing data model being trained based on the training device activity data and the fault history data from the operational support management repository. The exemplary computer-implemented method further includes outputting, in real time, the predicted operational support data object to the requesting client device.

[0005] Additionally or alternatively, in some exemplary embodiments, the exemplary computer-implemented method further includes receiving, through a requesting client device, a user input requesting the initiation of a problem support session, and the predicted operational support data object is output in response to receiving the user input requesting the initiation of the problem support session.

[0006] Additionally or alternatively, in some exemplary embodiments, the exemplary computer-implemented method further includes receiving, through the requesting client device, user input involving the operational support data object, and terminating the initiation of the defect support session in response to receiving the user input involving the operational support data object.

[0007] Additionally or alternatively, in some exemplary embodiments, the exemplary computer-implemented method further includes receiving updated fault text description data in response to user input updating the fault text description data, and upon receiving the fault text description data, automatically applying the device activity data and the updated fault text description data to an operational support processing data model in real time to select an updated predicted operational support data object from the operational support management repository, and outputting the updated predicted operational support data object to the requesting client device.

[0008] Additionally or alternatively, in some exemplary embodiments, the exemplary computer-implemented method further includes receiving support search data associated with the defect support session, where the support search data is further applied to the operational support process data model to select predicted operational support data objects.

[0009] Additionally or alternatively, in some exemplary embodiments, outputting the predicted operational support data objects to the requesting client device in real time includes causing the requesting client device to render a support user interface including a first sub-interface associated with the main support transmission process and a second sub-interface including the predicted operational support data objects.

[0010] Additionally or alternatively, in some exemplary embodiments, the exemplary computer-implemented method further includes identifying a set of operational support data objects, identifying training device activity data, and training an operational support process data model to identify a set of possible fault classification identifiers based at least on the training device activity data, and to associate each possible fault classification identifier of the set of possible fault classification identifiers with at least a portion of the set of operational support data objects.

[0011] Additionally or alternatively, in some exemplary embodiments, the dynamic home communications network includes a plurality of network-connected devices associated with a plurality of network-connected device types, and the operational support processing data model selects predicted operational support data objects based at least in part on the plurality of network-connected device types.

[0012] Additionally or alternatively, in some exemplary embodiments, the device activity data indicates a plurality of faults represented by a plurality of fault classification identifiers, and the predicted operational support data object is associated with a first fault classification identifier representing a first fault among the plurality of faults that contributes to each other fault among the plurality of faults.

[0013] Additionally or alternatively, in some exemplary embodiments, the exemplary computer-implemented method further includes identifying a user profile associated with the requesting client device and determining device activity data including at least device identification data for one or more network-connected devices associated with the dynamic home communications network based at least in part on the user profile.

[0014] Additionally or alternatively, in some exemplary embodiments, initiating a fault support session associated with the requesting client device further includes initiating a process for establishing a connection between the requesting client device and a technician device associated with the technician, where the predicted operational support data object is output prior to establishing the connection.

[0015] Additionally or alternatively, in some exemplary embodiments, the exemplary computer-implemented method further includes, in response to receiving user input involving the operational support data object, completing a process for establishing a connection between the requesting client device and the technician device.

[0016] According to a second aspect of the present disclosure, an apparatus is provided for selecting predicted operational support data objects from an operational support management repository using device activity data from a dynamic home communication network. In one exemplary embodiment of the apparatus, the exemplary apparatus includes at least one processor and at least one memory having computer-coded instructions stored therein. The computer-coded instructions, upon execution on the at least one processor, cause the apparatus to perform any one of the exemplary computer-implemented methods described herein. In another exemplary embodiment of the apparatus, the apparatus includes means for performing each operation of any one of the exemplary computer-implemented methods described herein.

[0017] According to a third aspect of the present disclosure, a computer program product is provided for selecting predicted operational support data objects from an operational support management repository using device activity data from a dynamic home communications network. In at least one exemplary embodiment of the computer program product, the exemplary computer program product includes at least one non-transitory computer-readable storage medium having computer program code stored thereon. The computer program code, upon execution on at least one processor, configures the computer program product to perform any one of the exemplary computer-implemented methods described herein.

[0018] Having thus described embodiments of the present disclosure in general terms, reference is now made to the accompanying drawings, which are not necessarily drawn to scale. [Brief description of the drawings]

[0019] [Figure 1] 1 illustrates a block diagram of a system that may be specially configured within which embodiments of the present disclosure may operate. [Diagram 2] 1 illustrates a block diagram of an exemplary fault support device that may be specially configured according to an exemplary embodiment of the present disclosure. [Diagram 3] 1 illustrates an example support user interface visualization for identifying and outputting at least one predicted operational support data object, in accordance with at least some embodiments of the present disclosure. [Figure 4] 14 illustrates another visualization of an example support user interface for identifying and outputting at least one predicted operational support data object, in accordance with at least some embodiments of the present disclosure. [Figure 5A] 1 illustrates an example dynamically updated support user interface visualization for identifying and outputting at least one predicted operational support data object, in accordance with at least some embodiments of the present disclosure. [Figure 5B]1 illustrates an example dynamically updated support user interface visualization for identifying and outputting at least one predicted operational support data object, in accordance with at least some embodiments of the present disclosure. [Figure 6] 1 illustrates an example data representation of operational support data object storage within an operational support management repository, in accordance with at least some embodiments of the present disclosure. [Figure 7] 1 illustrates an example data representation of an operational support data object associated with a fault classification identifier, according to at least some embodiments of the present disclosure. [Figure 8] 1 illustrates an example visualization of projected operational resource selection utilizing an operational support process data model, in accordance with at least some embodiments of the present disclosure. [Figure 9] 1 illustrates a flowchart showing example operations of an example process for applying device activity data and fault text description data to an operations support process data model to select predicted operations support data objects for output, according to at least some example embodiments of the present disclosure. [Figure 10] 1 illustrates a flowchart showing example operations of an example process for terminating an initiation of a problem support session, according to at least some example embodiments of the present disclosure. [Figure 11] 1 illustrates a flowchart depicting an example operation of an example process for dynamically outputting updated forecasted operational support data objects, in accordance with at least some example embodiments of the present disclosure. [Figure 12] 1 illustrates a flowchart showing example operations of an example process for applying supporting search data, according to at least some example embodiments of the present disclosure. [Figure 13] 1 illustrates a flowchart showing example operations of an example process for training an operational support process data model, in accordance with at least some example embodiments of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will now be described more fully hereinafter with reference to the accompanying drawings in which some, but not all, embodiments of the present disclosure are illustrated. Indeed, the present disclosure may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout.

[0021] overview A user may experience any number of malfunctions affecting one or more of the devices under his or her control. For example, a user may control any number of devices and / or systems, any of which may experience a malfunction. The devices and / or systems may experience slowed performance, hardware failures, software vulnerabilities (e.g., viruses, spyware, malware, etc.), software application crashes, incompatibilities with peripherals and / or other devices, connectivity issues with other devices, etc. In the context of a home network, such devices may be connected to the home network, thus increasing the likelihood and types of malfunctions that may occur. For example, devices and / or systems on the network may experience network connectivity failures and / or network drops, poor connectivity with the network, incompatibility with this type of network, etc. The network itself may experience any number of malfunctions. For example, the network may experience reduced communication capacity (e.g., reduced bandwidth, throttling, etc.), loss of connectivity with an external network (e.g., the Internet), blocked communication channels such as ports, etc.

[0022] In this regard, it should be understood that at any one time, a user may be forced to address any of a number of issues occurring individually or in parallel, each of which may require different expertise, resources, and / or capabilities to resolve, and the user may not be able to easily address each issue as it occurs.

[0023] In many contexts, such as a home network, devices of various types, makes, and models may be interconnected. At a given time, one or more of the devices that establish the home network may experience a malfunction, and such a malfunction may trigger others in a daisy-chain effect that may result in widespread instability of the network.

[0024] A user may not have the knowledge or experience to prioritize and address all of the faults associated with his / her device, system, and / or network. The user may seek assistance from a technical support professional (e.g., a service representative, etc.). Such technical support sessions suffer from unique deficiencies. For example, each device, system, and / or network may be associated with various technicians, and thus the user may need to identify the appropriate technician for a particular fault and / or the appropriate technician for each of numerous simultaneous faults. Additionally, contacting and communicating with technicians to resolve a fault is often time consuming and may be complicated or unsuccessful for any of a number of reasons (e.g., difficulty in communicating with the technician, the technician not receiving sufficient data to diagnose the fault, the technician's lack of knowledge on how to resolve the diagnosed fault, the technician's lack of knowledge on the structure of the network and its member devices, etc.).

[0025] Such deficiencies are exacerbated in the context of multiple network-connected devices, where multiple faults may exist simultaneously and / or have varying or compound faults. For example, a user may not be able to self-diagnose and / or resolve multiple faults associated with one or more devices, and may have to contact a first technician for a first fault, a second technician for a second fault, and so on. Each of these faults may or may not be successfully resolved independently, with the likelihood of success being highly dependent on the individual technical capabilities of the user experiencing such fault, the individual technical capabilities of the technicians to whom the user is connected, the communication capabilities of each party, and so on. Even in situations where all faults can be resolved, doing so may require a significant amount of time to communicate with each technician, diagnose the faults, and subsequently resolve each fault.

[0026] Embodiments of the present disclosure enable the selection and provision of predicted operational support data objects that are accurately determined to be likely to assist in resolving a particular fault of interest. Such embodiments deliver the predicted operational support data objects at the start of a fault support session that facilitates communication with a technical support representative, at a time when the predicted operational support data objects are most likely to be useful to the requesting user.

[0027] Embodiments of the present disclosure employ an operations support processing data model that is trained using a particular data set, e.g., device activity data and at least fault text description data, to determine particular faults to resolve and / or to select predicted operations support data objects that assist in resolving such faults. In some embodiments, the predicted operations support data objects may be provided and / or otherwise output by a requesting client device, e.g., such that the predicted operations support data objects may be accessed and utilized to resolve applicable faults.

[0028] The embodiments of the present disclosure reduce the level of technical expertise required by a user to diagnose, prioritize, and / or resolve a particular fault. By automatically detecting and / or parsing data and applying such data to a trained operational support processing data model described herein, the embodiments of the present disclosure can accurately identify faults that are likely to affect (or likely to affect in the future) one or more network-connected devices connected to or embodying a dynamic home communication network. Utilizing specific input data corresponding to a particular communication network, such as device activity data, support activity data, and / or historical data, such faults and corresponding operational support resources are identified at various levels of granularity with respect to technical faults for any of various types of faults without requiring additional user expertise to detect, prioritize, and / or resolve. Additionally or alternatively, in situations where multiple faults occur and / or interact with each other (e.g., in a compounding or daisy-chain effect), the embodiments of the present disclosure may detect such relationships from the detected, stored, and / or input data described herein without relying on user knowledge and / or expertise.

[0029] Embodiments of the present disclosure additionally or alternatively reduce and / or eliminate reliance on technical personnel. For example, embodiments of the present disclosure accurately identify data associated with any number of faults, regardless of device type, brand, etc., and predicted operational support data objects associated with such faults. In this regard, some embodiments of the present disclosure may identify and output predicted operational support data objects for resolving faults associated with any of such device types, brands, etc. Thus, by enabling the identification and output of operational support data objects associated with any number of devices of various device types, brands, etc., embodiments of the present disclosure enable better resolution of numerous faults without requiring difficult, and often difficult, communication with individual technical personnel, identification of such technical personnel, etc. Furthermore, in situations where embodiments provide operational support data objects to assist in resolving technical faults, such embodiments may entirely eliminate the need to identify and communicate with one or more technical personnel, avoiding the possibility that such technical personnel may be ineffective in resolving the fault due to lack of expertise, knowledge, etc.

[0030] Some embodiments of the present disclosure may further overcome certain technical constraints arising from a unique technical context for selecting and outputting predicted operational support data objects that may be accessed instead of initiating and maintaining a fault support session and / or may completely avoid the use of technical resources required to establish and maintain a fault support session. For example, in one exemplary context, a user initiates a fault support session seeking assistance with one or more specific faults. However, to avoid the computing resource costs associated with initiating and / or maintaining such a session, the predicted operational support data objects are output with low latency requirements. In this regard, predicted operational support data objects that are likely to assist in resolving one or more faults are output with sufficiently low latency such that the user may view and access at least one predicted operational support data object within a few seconds (e.g., in real time or near real time) before the fault support session is fully connected. Some embodiments of the present disclosure utilize low latency application of specific data models, such as operational support process data models, that are trained to utilize specific data (e.g., device activity data, fault text description data, other support activity data, etc.) that are retrievable and / or detectable in real time. Such data models therefore execute in real-time or near real-time, enabling accurate selection and / or output of predicted operational support data objects based on a variety of data regarding the user, the user's device, the user's communications network, the user's attempted support actions, etc.

[0031] It should be appreciated that by providing accurate selection and / or output of predicted operational support data objects, the operational support process data model provides each and every one of the technical improvements described herein. By specifically configuring the operational support process data model, the data model precisely performs such functionality that is specific to a particular communications network, e.g., specific to network-connected devices connected to the communications network, and / or embodied in the communications network itself.

[0032] One exemplary context in which embodiments of the present disclosure provide particular advantages is within the context of detecting and / or resolving faults associated with a home network and / or network-connected devices thereon.

[0033] The embodiments of the present disclosure provide numerous technical advantages in various technical fields. For example, the embodiments of the present disclosure accurately identify and select predicted operational support data objects that are likely to assist in resolving an identified fault. The output of such predicted operational support data objects reduces the level of technical competence that would traditionally be required to resolve such faults. Additionally or alternatively, some embodiments of the present disclosure utilize an operational support process data model that is specifically configured to perform such predicted operational support data object selection without requiring any additional input from a user. Furthermore, additional or alternatively, by providing selected predicted operational support resources that are determined with sufficient accuracy to be likely to assist in resolving one or more faults, such embodiments of the present disclosure can reduce and / or eliminate the need to fully initiate a fault support session between a client device associated with a user and a technician device associated with a particular technician to resolve such faults. In this regard, the embodiments of the present disclosure conserve computing resources of the client device, technician device, and / or intermediate device that initiates such a connection.

[0034] Additionally or alternatively, embodiments of the present disclosure provide operational support data objects at critical times (e.g., when a user indicates a need for operational support data objects, when a user has requested but not yet received technical assistance, etc.). In some contexts, for example, operational support data objects are provided during a support session initiation period that occurs after a request for session initiation but before the session is fully initiated. In this regard, operational support data objects are precisely determined and provided at specific times when such operational support data objects are most likely to be accessed.

[0035] Additionally or alternatively, embodiments of the present disclosure enable accurate identification of proprietary content (e.g., embodied in operational support data objects) in various contexts. For example, exemplary embodiments of the present disclosure provide operational support data objects for various types of connected network-connected devices on a particular communication network, daisy-chains of errors related to several associated network-connected devices, and / or otherwise compounded across various communication networks. Further, additionally or alternatively, embodiments provide relevant specific operational support data objects based on current data values ​​(e.g., live devices on or recently on the network, user text descriptions, errors resolved in the past, available content hosted locally and / or by third parties, etc.). Use of such current data may enable accurate identification, selection, and provision of operational support data objects that are most likely to involve the user, and may assist in resolving one or more faults without requiring an initiated support session connection.

[0036] Additionally or alternatively, embodiments of the present disclosure may eliminate significant time and / or resource burdens associated with user interaction with a support session. For example, some embodiments provide various technical advantages by providing an accurate list of predicted operational support data objects in real time or near real time at the start of a technical support session (e.g., within seconds during and / or before the start of a support session, or a process for maintaining a support session), such that the predicted operational support data objects may be easily accessed by the user during this critical period. In this regard, the time-related difficulties associated with providing accurate predicted operational support data objects are addressed by the embodiments described herein, enabling access to the predicted operational support data objects to reduce the likelihood that computing resources would be further consumed to fully initiate and / or maintain an ongoing support session, or to completely eliminate the need for computing resources to be further consumed. Some embodiments described herein provide further advantages in the area of ​​reliability of data content storage and retrieval, by maintaining and / or selecting third-party operational support data objects that may correspond to data maintained and / or made available by individual, disparate, and uncorrelated external data systems.

[0037] definition In some embodiments, some of the above operations may be modified or further extended. Furthermore, in some embodiments, additional optional operations may be included. Modifications, extensions, or additions to the above operations may be performed in any order and in any combination.

[0038] Many modifications and other embodiments of the disclosure described herein will come to mind to one skilled in the art to which the disclosure pertains having the benefit of the teachings presented in the foregoing description and the associated drawings. Thus, it should be understood that the embodiments are not to be limited to the specific embodiments disclosed, and that modifications and other embodiments are intended to be included within the scope of the appended claims. Moreover, while the foregoing description and the associated drawings describe exemplary embodiments in the context of certain example combinations of elements and / or features, it should be understood that different combinations of elements and / or features may be provided by alternative embodiments without departing from the scope of the appended claims. In this regard, for example, it is contemplated that combinations of elements and / or features other than those expressly described above may be recited in some of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.

[0039] The term "user" refers to an entity that controls one or more devices. Non-limiting examples of users include an individual, an organization, or a group of people that control client devices that have access to a communications network. A user is associated with a "user identifier" and / or a "user profile" that uniquely represents the user within a computing environment.

[0040] The term "requesting client device" refers to a computing device embodied in hardware, software, firmware, and / or combinations thereof that enables access to one or more client devices, systems, and / or supporting functionality associated with one or more communications networks. A client device may execute a browser application configured to access web-based applications that provide such supporting functionality, and / or execute native applications that provide the supporting functionality and / or that may also communicate with web-based applications.

[0041] The term "user input" refers to any user interaction with a client device that initiates a process through the client device. Non-limiting examples of user input include user gestures via touch zones or interactive displays (e.g., taps, swipes, pinches, multi-touch, multi-taps, and custom gestures), voice commands, peripheral input, keyboard presses, mouse clicks, video-detected actions, and data entry.

[0042] The term "communications network" refers to one or more interconnected computing devices, embodied in hardware, software, firmware, and / or combinations thereof, that enable the transmission of data between such one or more computing devices. Non-limiting examples of communication networks include public networks (e.g., the Internet), private networks (e.g., home networks, enterprise networks), cellular networks, and hybrid networks.

[0043] The term "home communications network" refers to a communications network associated with one or more user identifiers that defines network access within the home environment of a user associated with the user identifier. A home communications network embodies an internal network and / or sub-network (e.g., a sub-network of the Internet) that may include any number of network-connected devices of various device types, each of which may be owned and / or operated by the user identifier that controls the home communications network and / or may be owned and / or operated by another user identifier. At a given time, the home communications network includes an "active network-connected device set" that includes all network-connected devices that are currently connected to the home communications network for communication purposes, and an "inactive network-connected device set" that includes all network-connected devices that can be connected to the home communications network and / or that were previously connected to the home communications network but are not currently connected to the home communications network.

[0044] The term "network-connected device" refers to a computing device that is connected to or otherwise a part of a communications network. Non-limiting examples of network-connected devices include client devices for one or more end users of a communications network, routers, switches, relays, base stations, intracontinental and / or transcontinental network wiring, communications satellites, and cellular communications towers. The term "set of network-connected devices," when used with respect to a particular communications network, refers to one or more network-connected devices of that communications network.

[0045] The term "device identification data" refers to data and / or metadata that uniquely identifies a network-connected device associated with a communications network. Non-limiting examples of device identification data include a device identifier, an IP address, and an IMEI.

[0046] The term "device activity data" refers to electronically managed data representing system-initiated and / or user-initiated actions that affect configuration data of network-connected devices associated with a communications network or that are indicative of attempts to resolve one or more fault classification identifiers associated with network-connected devices associated with a communications network.

[0047] The term "support activity data" refers to electronically managed data representing user-initiated actions associated with initiating and / or receiving technical support for a fault classification identifier. Non-limiting examples of support activity data include one or more search queries entered by a user for operational support data objects associated with a fault classification identifier, data representing user interactions with a support user interface, chat log data of a fault support session between a user utilizing a client device and a technician utilizing a technician device, and user interactions with an automated system for providing technical support data and / or help.

[0048] The term “operations support processing data model” refers to a statistical, algorithmic, and / or machine learning model specifically trained to identify associations between data indicative of potential fault classification identifiers of one or more network-connected devices on a communications network and any number of third-party operations support data objects that may be used to resolve or improve the potential fault classification identifiers.

[0049] The term "predicted operational support data object" refers to electronically managed data and / or instructions identified as likely to assist in resolving one or more faults. In some embodiments, the operational support data object is identified by an operational support process data model associated with a confidence score for resolving and / or improving an associated possible fault classification identifier when the confidence score is above a certain minimum confidence threshold. Non-limiting examples of predicted operational support data objects include data files (e.g., PDF, DOC, or other formats of mixed data files) containing text, images, videos, etc., web pages, uniform resource locators or other web links, computer executable instructions, computer applications, image files (e.g., PNG, JPG, or other image formats), and video files (e.g., MP4, MOV, AVI, or other video file formats). A user may access and / or utilize the predicted operational support data object to perform a self-help action to resolve one or more faults.

[0050] The term "fault classification identifier" refers to electronically managed data that uniquely represents a technical operational problem of a particular device or system and / or an interoperability problem between devices of a system. Non-limiting examples of fault classification identifiers include problems with connecting a computing device to a communications network, interoperability problems between a first computing device and a second computing device, interoperability problems or connectivity failures between a computing device and a peripheral device, performance hardware components of a computing device below a certain threshold, degradation in performance of a hardware component of a computing device over a certain time interval or upon the occurrence of a certain event represented in device activity data, software application crashes, unexpected shutdown of a computing device, loss of network connectivity of a computing device, and the presence of malware, spyware, computer viruses, etc. In some embodiments, there are system operational support classification identifiers that identify multiple levels of granularity, such that a first system operational support classification identifier includes one or more subsystem operational support classification identifiers. In a non-limiting exemplary context, a system operations support classification identifier embodying a “printer problem” class of technical problem is associated with various sub-identifiers embodying particular problem types (e.g., “printer connectivity problem”, “printer printing problem”, “printer ink problem”, etc.) and / or problems for particular instances of devices and / or systems (e.g., “printer brand A printing problem” and “printer brand B printing problem”, and / or “printer brand A model 1 printing problem” and “printer brand A model 2 printing problem”).

[0051] The term "operational support data object" refers to electronically managed data that may be utilized to embody or retrieve text content data, web page data, video data, audio data, data instructions, or software applications to improve, resolve, and / or troubleshoot one or more fault classification identifiers associated with one or more computing devices. "Third-party operational support data object" refers to operational support data objects maintained on a data system separate from a particular data system to provide support functionality associated with a client device and / or communications network.

[0052] The term "operational support data object set," when used in reference to a particular fault classification identifier, refers to any number of third-party operational support data objects that may be utilized to improve or otherwise resolve the fault classification identifier.

[0053] The terms "operations support management repository" and "system operations support management repository" refer to one or more electronically maintained databases embodied in hardware, software, firmware, and / or combinations thereof that store any number of operations support data objects and / or associations between operations support data objects and operations support classification identifiers. In one non-limiting exemplary context, an operations support management repository includes operations support data objects each stored with an operations support classification identifier that embodies a fault classification identifier that the operations support data object is determined to resolve.

[0054] The term "problem support session" refers to an authorized connection between a client device and a technician device that allows a technical support technician to be provided to a user of the client device via the technician device. The problem support session allows data transfer between the client device and the technician device, which may include text data, video data, access control to the client device, and / or configuration of one or more network devices that can communicate via the client device.

[0055] The term "fault text description data" refers to text data transmitted as part of a fault support session by a client device and / or a technician device associated with the fault support session. Fault text description data includes text data entered by a user, including free-form text data and / or text data selected from a predefined set of available text elements.

[0056] The term "support session initiation period" refers to a period of time defined by the problem support system after receiving a user request to initiate a problem support session, but before the problem support session is actually established with the requesting client device. In some embodiments, the support session initiation period is configured as an intermediate period during which predicted operational support data objects are displayed to the user before the problem support system operates to establish a problem support session, or in parallel with the problem support system operating to establish a problem support session. In one exemplary context, the support session initiation period refers to a period of time after a user requests to initiate a problem support session, but before selecting a particular technician device with which to establish a connection, and / or before a connection is established with a particular technician device. In some embodiments, the end of the support session initiation period is represented by the time the problem support session is established with a particular technician device or technician.

[0057] The term "support search data" refers to electronically managed data entered via a client device that is associated with a user search for technical support associated with one or more fault classification identifiers. In some embodiments, the support search data includes user-entered text data that represents the user's description of the fault classification identifiers. The support search data is one exemplary type of fault text description data.

[0058] The term "support user interface" refers to a user interface that includes one or more interface elements associated with providing access to a problem support session. In some embodiments, the support user interface includes multiple sub-interfaces, each of which provides access to various data and / or functionality associated with providing technical support functionality.

[0059] The term "main support transmission process" refers to a computer-driven process for initiating, maintaining, and engaging in a fault support session. The main support process runs separately from one or more secondary support processes that operate in parallel with the main support process. Non-limiting examples of secondary support processes include a process that provides operational support data objects that are dynamically associated with one or more identified fault classification identifiers as a user engages in the main support transmission process.

[0060] The term "training device activity data" refers to electronically managed data representing all or a portion of the available device activity data utilized to train a particular operational support process data model. During training, a training set of device activity is processed by the operational support process data model, enabling the operational support process data model to identify data trends, patterns, and / or other links in the training set of device activity data.

[0061] Exemplary Systems and Apparatus of the Disclosure FIG. 1 illustrates a block diagram of a system, which may be specially configured, within which an embodiment of the present disclosure may operate. Specifically, FIG. 1 illustrates an exemplary system 100 configured to enable selection and provision of predicted operational support data objects. The system 100 includes a fault support system 102, an external data system 112, a client device 104, any number of network-connected devices, including a printer 106A, a smartphone 106B, a tablet 106C, and one or more other network-connected devices 106D (the network-connected devices 106A-106D are collectively referred to as "network-connected devices 106"). The network-connected devices 106 can communicate with each other and / or with one or more other devices, such as the client device 104, via a first communication network 110. The fault support system 102 can communicate with the external data system 112 and / or with one or more other devices, such as the client device 104, via a second communication network 108.

[0062] The fault support system 102 includes one or more computing devices embodied in hardware, software, firmware, and / or combinations thereof that provide predicted operational support data object selection and provision functionality. For example, the fault support system 102 may embody or be otherwise included in a system that provides user automated support and / or technician-based support associated with one or more network-connected devices. The fault support system 102 trains an operational support process data model, maintains the trained operational support process data model, and utilizes the operational support process data model to select one or more predicted operational support data objects and / or output predicted operational support data objects. The fault support system 102 may provide such functionality to a client device, such as client device 104, associated with any number of computing devices, such as one or more of the network-connected devices 106. In some embodiments, the defect support system 102 maintains one or more repositories that store operational support data objects, data links for accessing operational support data objects (including third-party operational support data objects), associations between operational support data objects and defect classification identifiers, and / or correlations between device activity data, support activity data (e.g., including defect text description data), and defect classification identifiers.

[0063] The external data systems 112 may include any number of data systems external to the fault support system 102. Each external data system of the external data systems 112 may include one or more computing devices embodied in hardware, software, firmware, and / or combinations thereof that host, store, and / or otherwise provide access to one or more operational support resources. For example, in some embodiments, the external data systems 112 include one or more third-party web servers that host content associated with a particular fault. Such content may include web pages, videos, images, articles, manuals, and / or other textual content, applications that attempt to diagnose and / or resolve a particular fault, etc. It should be understood that each external data system may be controlled by a different entity and / or each external data system may maintain operational support data objects associated with a particular fault. For example, each external data system controlled by a particular entity embodying a device manufacturer may maintain operational support data objects associated with devices and / or systems provided by the device manufacturer. Alternatively or additionally, an external data system embodying, for example, a technical support forum platform may include operational support data objects associated with various faults for different types, makes, models, and other variations of devices.

[0064] Alternatively or additionally, in some embodiments, the external data system 112 includes any number of data systems that store data received, scraped, and / or otherwise identified by the fault support system 102. Data identified from such external data systems 112 may be used to identify fault classification identifiers likely to affect one or more network-connected devices and / or to identify predicted operational support data objects most likely to assist in resolving faults associated with one or more fault classification identifiers. For example, the external data systems 112 may include social media systems, web host blog systems, news systems, etc. that create and / or make available digital content associated with particular faults. In this regard, the fault support system 102 may receive and process such data to generate and / or identify fault classification identifiers associated with particular network-connected devices that are indicated as being general, affecting multiple devices associated with various individuals, being particularly severe or of high importance, etc. For example, the fault support system 102 may identify social media data, news article data, etc. from various systems of the external data systems 112, all such data indicating a particular fault that has recently affected many or all devices of a particular device type. In this regard, the fault support system 102 may utilize such data to adjust the likelihood that a predicted operational support data object associated with a particular fault (e.g., linked to a fault classification identifier corresponding to a particular fault) will be provided if associated with a particular user profile. For example, the fault support system 102 may increase the likelihood that such a predicted operational support data object will be provided in situations where device activity data associated with a user profile indicates ownership of a device of a particular device type and / or where device activity data and / or support activity data indicates the presence of a fault associated with a device of a particular device type.In some embodiments, the fault support system 102 utilizes such data to train one or more models as described herein to, for example, increase the likelihood that such models will select predicted operational support data objects associated with the fault support classification identifier that represent a particular fault that is “trending” (e.g., based on identifying several posts, articles, or other data that consider a particular fault to be above a certain threshold) or that is otherwise indicated as affecting a large number of users.

[0065] The client device 104 may include any number of computing devices embodied in hardware, software, firmware, and / or combinations thereof that provide user access to the functionality of one or more of the fault support system 102 and / or the network-connected devices 106. In some embodiments, the client device 104 is embodied by a user device owned, operated, and / or otherwise controlled by a particular user. Non-limiting examples of the client device 104 include specially configured smartphones, personal computers, tablets, laptops, smart watches, smart televisions, wearables, virtual reality devices, virtual assistant devices, and the like. The client device 104 may be specially configured to provide access to such functionality through one or more software applications (e.g., “apps”) installed on and / or otherwise executable by the client device 104. In some embodiments, the client device 104 includes or is capable of communicating with one or more connected devices that provide processing, communication, network connectivity, display, and / or other functionality. For example, the client device 104 may include a smartwatch paired with a smartphone that displays information processed and / or acquired by the smartphone and transmitted from the smartphone to the smartwatch via a short-range communications network (e.g., a Bluetooth® connection).

[0066] In some embodiments, the client device 104 is associated with a particular user profile. The user profile may be utilized to associate with the client device 104 particular data to be collected and / or otherwise processed by the fault support system 102. The user profile may be automatically created and / or assigned (e.g., based on a device identifier corresponding to the client device 104) or may be generated in response to a particular action by a user associated with the client device (e.g., upon registration of the user profile with the fault support system 102). In some embodiments, the user profile is used to associate particular device identification data for network-connected devices owned and / or controlled by a particular user of the client device 104, to identify particular communication networks (e.g., dynamic home communication networks) controlled by the user and / or its network-connected devices, to initiate particular functionality of the fault support system 102, etc. It should be appreciated that in situations where particular data is linked to a user profile, such data may then be utilized to limit and / or weight particular data associated with the user profile. For example, device identification data indicative of the presence of particular network-connected devices that are active and / or inactive for a particular dynamic home communications network may be stored by the trouble support system 102 associated with a particular user profile corresponding to the client device 104. Thereafter, upon initiation of a particular functionality as described herein (e.g., the initiation of a trouble support session), the trouble support system 102 may retrieve and utilize such data and apply such data to a particular data model that generates a higher weighting for operational support data objects related to the network-connected devices identified by such data stored in association with the user profile.

[0067] The communications network 108 may include any number of computing devices embodied in hardware, software, firmware, and / or combinations thereof, and the communications network 108 may enable the transmission of data to and / or from one or more other devices connected to the computing devices. For example, as shown, the communications network 108 may enable the transmission of data between the fault support system 102 and / or the external data system 112. Additionally or alternatively, the communications network 108 may enable the transmission of data between the client device 104 and the fault support system 102. Additionally or alternatively, in some embodiments, the communications network 108 may enable the transmission of data between the client device 104 and some or all of the external data systems 112.

[0068] The communications network 108 may embody any of a number of network configurations. In some embodiments, the communications network 108 embodies a public network (e.g., the Internet). In some embodiments, the communications network 108 embodies a private network (e.g., an internal network between certain devices). In some other embodiments, the communications network 108 embodies a hybrid network (e.g., a network that allows internal communication between certain connected devices and external communication with other devices). The communications network 108 may include one or more base stations, repeaters, routers, switches, cell towers, communications cables, and / or associated routing stations, etc. In some embodiments, the communications network 108 includes one or more user-controlled computing devices (e.g., user-owned routers and / or modems) and / or one or more external utility devices (e.g., Internet service provider devices).

[0069] The communications network 110 may embody a private network that enables communication between various network-connected devices 106 and the client device 104. In some embodiments, for example, the communications network 110 embodies a home network that enables communication of various devices on the home network, such as a network-connected printer (network-connected device 106A), the user's smartphone (network-connected device 106B), the user's tablet (network-connected device 106C), other users' smartphones, personal computers, laptops, smart televisions, and / or other Internet of Things-enabled devices, virtual assistant devices, home security systems, and other network-connected devices 106D. A user may utilize one or more such devices independently and / or access it through another device connected to the communications network 110, for example, through interaction with the client device 104.

[0070] The device activity data may be detected and / or otherwise received by the fault support system 102 associated with any one or more of the communications network 110, the client device 104, and / or the network-connected devices 106. For example, in some embodiments, device activity data associated with each network-connected device connected to the communications network 110 and / or associated with components of the communications network 110 itself is detected, requested, and / or otherwise received by the client device 104 for transmission to the fault support system 102. Alternatively or additionally, in some embodiments, the fault support system 102 directly monitors the communications network 110 to identify device activity data associated with the communications network 110 and / or the network-connected devices 106 capable of communicating with the communications network 110. A user may utilize the client device 104 to update configurations and / or otherwise affect the operation of one or more of the network-connected devices 106, and device activity data indicative of such configuration updates (e.g., a configuration log) may be included in the device activity data processed by the system 100.

[0071] Additionally or alternatively, in some embodiments, support activity data is generated based on one or more initiated actions associated with diagnosing and / or resolving one or more faults. In some embodiments, support activity data (fault text description data entered through client device 104 during a fault support session) representative of, for example, initiated search queries for support regarding the fault (e.g., performed by a search engine), interactions with one or more support processes of fault support system 102 and / or associated systems may be generated by and / or received from client device 104. Support activity data and / or device activity data may be generated by any of the devices as shown and described herein and received and / or otherwise stored by fault support system 102 for processing to select one or more predicted operational support data objects as described herein.

[0072] At any given time, one or more of the network-connected devices 106 may experience a malfunction and / or the communications network 110 itself may experience a malfunction. For example, one or more of the network-connected devices 106 may operate at a reduced capacity due to any of a number of physical and / or virtual factors, such as (1) incompatibility of hardware, software, firmware, etc., (2) reduced hardware components, and (3) operation of malicious software, such as spyware, malware, viruses, etc. Alternatively or additionally, one or more of the network-connected devices 106 may experience a network connectivity error. For example, the network-connected device 106A may lose connection with the communications network 110 due to any of a number of malfunctions, such as loss of signal by the network-connected device 106A, a hardware component for connecting the network-connected device 106A to the communications network 110 that has failed, a configuration change that prevents the network-connected device 106A from reconnecting to the communications network 110, etc. Additionally or alternatively, in some embodiments, the communications network 110 itself may experience one or more malfunctions, such as a loss of power by one or more devices embodying the communications network 110, a loss of connection by the communications network to an external network (e.g., an Internet outage), a reconfiguration of one or more devices of the communications network 110 that prevents communication of traffic to and / or from one or more of the network-connected devices 106A, etc.

[0073] Additionally or alternatively, each of the network-connected devices 106 may experience different types of malfunctions. For example, a smart printer (e.g., embodied by network-connected device 106A) may experience particular operational problems that are different from those experienced by a smartphone (e.g., embodied by network-connected device 106B). In this regard, as the number of different types of network-connected devices on a particular communications network increases, the complexity of possible malfunctions that may arise and / or need to be resolved increases.

[0074] It should be understood, therefore, that as the complexity of network-connected devices increases (e.g., the number and / or the variability of devices having different characteristics increases), such technical complexity is particularly prevalent in the context of home networks. For example, in the context of a home network embodied by communication network 110, network-connected devices 106 may include any number of network-connected devices, each of various device types, brands, models, operations, etc. Additionally or alternatively, one or more of such devices may actively communicate over the network, while other network-connected devices may be inactive and / or not otherwise communicate over the network. Client device 104 utilizes a system operational support data model to enable interaction with the fault support system, as described herein, to accurately identify and / or output predicted operational support data objects to assist in resolving any one or more of the various faults.

[0075] Additionally or alternatively, the communications network 110 may embody a dynamic home communications network associated with a periodically changing list of actively connected network-connected devices ("active network-connected devices") and inactive network-connected devices that are not connected to the communications network 110. For example, a user handheld device may periodically disconnect from the communications network 110 as the user handheld device is relocated (e.g., to reach outside the range of the communications network 110) and / or may dynamically reconnect (e.g., upon re-entering the range of the communications network 110). In this regard, device activity data indicative of active network-connected devices at a particular time point and / or inactive network-connected devices at any particular time point may be identified, retrieved, and / or otherwise received. In some embodiments, such data may be utilized to identify particular network-connected devices of the communications network 110. For example, the inactive and active network-connected devices may be compared over one or more time intervals to determine fixed components of the communications network 110, such as routers, modems, etc., that may be configurable to address failures associated with one or more network-connected devices and / or the network connectivity of the communications network 110 itself.

[0076] 2 illustrates a block diagram of an exemplary fault support device that may be specially configured according to an exemplary embodiment of the present disclosure. In some embodiments, the fault support system 102 is embodied by one or more computing systems, such as the fault support device 200 shown and described in FIG. 2. The fault support device 200 includes a processor 202, a memory 204, an input / output circuit 206, a communication circuit 208, and a support providing circuit 210. The fault support device 200 may be configured to perform the operations described herein using one or more of the sets of circuits 202, 204, 206, 208, and / or 210.

[0077] Although these components are described in terms of functional limitations, it should be understood that a particular implementation necessarily involves the use of specific computing hardware. It should also be understood that some of the components described herein may include similar or common hardware. For example, two sets of circuits may both leverage the use of the same processor, network interface, storage medium, etc. to perform the associated functions of those sets, thus not requiring duplicated hardware for each set of circuits. Thus, users of the term "circuitry" as used herein with respect to components of an apparatus should be understood to include specific hardware configured to perform the functions associated with the particular circuitry as described herein.

[0078] In particular, the term "circuitry" should be broadly understood to include hardware and, in some embodiments, software for configuring hardware. For example, in some embodiments, "circuitry" includes processing circuitry, storage media, network interfaces, input / output devices, etc. Alternatively or additionally, in some embodiments, other elements of fault support apparatus 200 may provide or supplement the functionality of another particular set of circuits. For example, in some embodiments, processor 202 provides processing functionality for any of the sets of circuits, memory 204 provides storage functionality for any of the sets of circuits, communication circuitry 208 provides network interface functionality for any of the sets of circuits, etc.

[0079] In some embodiments, the processor 202 (and / or a co-processor, or any other processing circuitry that assists or is otherwise associated with the processor) may communicate with the memory 204 via a bus for passing information between components of the fault support apparatus 200. In some embodiments, for example, the memory 204 may be non-transitory, for example, including one or more volatile and / or non-volatile memories. In other words, for example, the memory 204 in some embodiments includes or embodies an electronic storage device (e.g., a computer-readable storage medium). In some embodiments, the memory 204 is configured to store information, data, content, applications, instructions, etc., to enable the fault support apparatus 200 to perform various functions in accordance with exemplary embodiments of the present disclosure.

[0080] Processor 202 may be embodied in a number of different ways. For example, in some embodiments, processor 202 may include one or more processing devices configured to execute independently. Additionally or alternatively, in some embodiments, processor 202 includes one or more processors configured in tandem via a bus to enable independent execution of instructions, pipelines, and / or multithreading. Use of the terms "processor" and "processing circuitry" may be understood to include a single core processor, a multi-core processor, multiple processors internal to defect support apparatus 200, and / or one or more remote or "cloud" processors external to defect support apparatus 200.

[0081] In an exemplary embodiment, the processor 202 may be configured to execute instructions stored in the memory device 204 or otherwise accessible to the processor. Alternatively or additionally, the processor 202 may be configured to execute hard-coded functionality. Thus, whether configured by hardware or software methods, or a combination thereof, the processor 202 may represent an entity (e.g., physically embodied in a circuit) capable of performing operations according to embodiments of the present disclosure, while being configured accordingly. Alternatively or additionally, as another example, in some embodiments, when the processor 202 is embodied as an executor of software instructions, the instructions may specifically configure the processor 202 to execute algorithms embodied in specific operations described herein when such instructions are executed.

[0082] As one particular example, the processor 202 may be configured to perform various operations associated with selecting and providing improved predicted operational support data objects, e.g., as described with respect to the operation of the fault support system 102 and / or as further described herein. In some embodiments, the processor 202 includes hardware, software, firmware, and / or combinations thereof that receive and / or retrieve device activity data associated with a particular client device, user profile, etc. Additionally or alternatively, in some embodiments, the processor 202 includes hardware, software, firmware, and / or combinations thereof that receive and / or retrieve support activity data associated with a particular client device, user profile, etc. Additionally or alternatively, in some embodiments, the processor 202 includes hardware, software, firmware, and / or combinations thereof that maintain one or more data repositories of operational support data objects and / or associations of operational support data objects. Additionally or alternatively, in some embodiments, the processor 202 includes hardware, software, firmware, and / or combinations thereof that maintain an operational support process data model. Additionally or alternatively, in some embodiments, processor 202 includes hardware, software, firmware, and / or combinations thereof that initiate and / or maintain a problem support session. Additionally or alternatively, in some embodiments, processor 202 includes hardware, software, firmware, and / or combinations thereof that correlate device activity data and problem text description data to a particular problem support session. Additionally or alternatively, in some embodiments, processor 202 includes hardware, software, firmware, and / or combinations thereof that apply input data, such as device activity data and problem text description data, to an operational support process data model in real time.Additionally or alternatively, in some embodiments, the processor 202 includes hardware, software, firmware, and / or a combination thereof that outputs predicted operational support data objects selected by the operational support process data model in real time.

[0083] In some embodiments, the fault support apparatus 200 includes an input / output circuit 206 that communicates with the processor 202 to provide output to a user and, in some embodiments, may receive an indication of a user input. The input / output circuit 206 may include a display that may include one or more user interfaces and may include interfaces rendered as a web user interface, an application user interface, a user device, a back-end system, or the like. In some embodiments, the input / output module 206 may also include a keyboard, a mouse, a joystick, a touch screen, a touch area, soft keys, a microphone, a speaker, or other input / output mechanisms. The processor 202 and / or the input / output circuit 206 including the processor may be configured to control one or more functions of one or more user interface elements via computer program instructions (e.g., software and / or firmware) stored in a processor-accessible memory (e.g., memory device 204, etc.). In some embodiments, the input / output circuit 206 includes or utilizes a user-facing application to provide input / output functionality to a client device and / or other display associated with the user.

[0084] The communication circuitry 208 may be any means, such as a device or circuit embodied in either hardware or a combination of hardware and software, configured to receive and / or transmit data to and from a network and / or any other device, circuit, or module in communication with the fault support apparatus 200. In this regard, the communication circuitry 308 may include, for example, a network interface for enabling communication with a wired or wireless communication network. For example, the communication circuitry 208 may include one or more network interface cards, antennas, buses, switches, routers, modems, and supporting hardware and / or software, or any other device suitable for enabling communication over one or more networks. Additionally or alternatively, the communication circuitry 208 may include circuitry for interacting with an antenna and / or other hardware or software to cause transmission of signals via the antenna or process reception of signals received via the antenna. In some embodiments, the communication circuitry 208 communicates with the fault support apparatus 200 to enable transmission of data to and / or reception of data from a client device.

[0085] The support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof that support various functionalities associated with improved selection and / or provision of predicted operational support data objects. For example, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for receiving one or more input data sets for processing by the operational support process data model. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for initiating and / or maintaining a defect support session. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for correlating device activity data and defect text description data to a particular defect support session. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for applying device activity data and defect text description data to the operational support process data model in real time. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or combinations thereof for outputting predicted operational support data objects selected by the operational support process data model in real time.

[0086] Further, additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or a combination thereof for receiving user input indicating engagement with a predicted operational support data object. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or a combination thereof for initiating and terminating a fault support session. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or a combination thereof for receiving and processing updated device activity data and / or support activity data. Additionally or alternatively, in some embodiments, the support providing circuitry 210 includes hardware, software, firmware, and / or a combination thereof for training an operational support processing data model.

[0087] It should be understood that in some embodiments, the support providing circuitry 210 may include a separate processor, a specially configured field programmable gate array (FPGA), or a specially programmed application specific integrated circuit (ASIC). Additionally or alternatively, in some embodiments, one or more of the sets of circuits 202-210 may be combined. Alternatively or additionally, in some embodiments, one or more of the sets of circuits perform some or all of the functionality described in association with another component. For example, in some embodiments, one or more of the sets of circuits 202-210 are combined into a single module embodied in hardware, software, firmware, and / or combinations thereof. Similarly, in some embodiments, one or more of the sets of circuits, e.g., the support providing circuitry 210, are combined such that the processor 202 performs one or more of the operations described above with respect to each of these modules.

[0088] Exemplary Interfaces of the Present Disclosure Having described exemplary systems and devices according to the present disclosure, exemplary interfaces according to the present disclosure will now be considered. Each user interface may be renderable by any of a number of displays. For example, in some embodiments, the user interfaces may be renderable by the client device 104 and / or the fault support apparatus 200. In some embodiments, the fault support apparatus 200 configures and / or otherwise causes the rendering of the particular user interface shown. For example, in some embodiments, the fault support apparatus 200 outputs data for rendering by a display of the fault support apparatus 200. Alternatively or additionally, in some embodiments, the fault support apparatus 200 outputs data to a client device for rendering by a display of the client device.

[0089] 3 illustrates an exemplary support user interface visualization for identifying and outputting at least one predicted operational support data object according to at least some embodiments of the present disclosure. Specifically, FIG. 3 illustrates an exemplary support user interface 300. The exemplary support user interface 300 may be rendered on a client device during communication between the client device and the defect support apparatus 200, the client device communicating with the defect support apparatus 200 to access predicted operational support data object selection and provision functionality, and / or other support functionality. For example, the client device may render the support user interface 300 within a specially configured native application associated with the functionality of the defect support apparatus 200 and / or within a browser application utilized to access a web-based application associated with the functionality of the defect support apparatus 200.

[0090] As illustrated, the exemplary support user interface 300 includes a first sub-interface 302. The first sub-interface is associated with displaying interface elements associated with a main support transmission process. The main support transmission process may include information entered by a user associated with a fault for which support is to be provided. The user may submit various information associated with the fault to be resolved to the fault support device 200 and / or may receive data in response to such information associated with a particular fault classification identifier corresponding to such fault. In this regard, the first sub-interface 502 may be dynamically updated as the user enters information into the fault support device 200 and / or receives response data from the fault support device 200.

[0091] As illustrated, the first sub-interface 302 illustrates interface elements associated with a main support transmission process that embodies interactions between a user and an automated system that assists the user in diagnosing faults and / or resolving such diagnosed faults. In some embodiments, a user may interact with such an automated system to identify a particular fault to resolve, and the user may then be connected to an expert (e.g., a technician) that can assist the user in resolving the identified fault. Alternatively or additionally, in some embodiments, a user may interact with such an automated system to identify a particular fault and receive automated instructions for resolving the identified fault.

[0092] As illustrated, the first sub-interface 302 includes various representations of fault text description data, specifically, fault text description elements 304A, 304B, 304C, 304D, and 304E (collectively, "fault text description elements 304"). The fault text description elements 304B and 304D represent fault text description data entered by a user. The fault text description elements 304A, 304C, and 304E represent fault text description data provided by the fault support device 200. In this regard, the fault text description elements 304 embody a conversation associated with diagnosing and / or resolving a particular fault. The fault text description data provided by the fault support device 200 may be predetermined, may be determined based on a particular rule set, and may be generated by an artificial intelligence and / or machine learning model specifically configured to generate fault text description data in response to text received from a user associated with a particular fault. As illustrated, fault text description element 304 indicates that a user is experiencing a fault associated with their printer (e.g., as shown in fault text description element 304B), specifically, a “Printer Brand A, Model 1” printer (e.g., as shown in fault text description element 304D).

[0093] The exemplary support user interface 300 further includes a second sub-interface 352. The second sub-interface 352 includes interface elements associated with any number of operational support data objects. The second sub-interface 352 includes various interface elements each associated with a predicted operational support data object determined to assist and / or otherwise selected to assist in resolving the identified fault. Specifically, the second sub-interface 352 includes a first operational support element 354A associated with the first predicted operational support data object, a second operational support element 354B associated with the second predicted operational support data object, and a third operational support element 354C associated with the third predicted operational support data object (collectively, "operational support elements 354"). Each of the operational support elements 354 is associated with an operational support data object selected by the fault support device 200 as being associated with and / or useful in resolving the printer fault encountered by the user.

[0094] One or more of the predicted operational support data objects may correspond to third-party operational support data objects hosted and / or otherwise made available by an external data system. In this regard, the corresponding operational support element may provide a link for accessing the third-party operational support data object upon interaction by a user. For example, as illustrated, a first operational support element 354A is associated with a first operational support data object maintained and / or otherwise available at a first URL "www.techsite#1.com / printer," and thus, a user may interact with the first operational support element 354A to retrieve and / or otherwise access the first operational support data object via this URL. Similarly, the second operational support element 354B is associated with a second operational support data object maintained and / or otherwise available at a second URL, "www.videosite#1.com / watch?A," such that a user may interact with the second operational support element 354B to retrieve and / or otherwise access the second operational support data object via this URL. Additionally, the third operational support element 354C is associated with a third operational support data object maintained and / or otherwise available at a third URL, "www.brandAprinter.com / guides / A1," such that a user may interact with the third operational support element 354C to retrieve and / or otherwise access the third operational support data object via a corresponding URL. It should be appreciated that each of these URLs may correspond to data objects hosted by different systems and may be associated with one or more different entities. In this regard, the second sub-interface 352 provides a centralized access point to various data objects related to the particular fault the user is experiencing.

[0095] In some embodiments, the fault support apparatus 200 selects one or more operational support data objects made accessible via the support user interface 300 via one or more portions of data available to the fault support apparatus 200. For example, in some embodiments, the fault support apparatus 200 selects the predicted operational support data object based at least in part on fault text description data entered by a user (e.g., fault text description data presented in the corresponding first sub-interface 302). Additionally or alternatively, in some embodiments, the fault support apparatus 200 selects the predicted operational support data object based at least in part on device activity data associated with a particular user and / or communication network retrieved as described herein. Alternatively or additionally, in some embodiments, the fault support apparatus 200 selects the predicted operational support data object () based at least in part on other support activity data associated with a particular user as described herein. The fault support apparatus 200 may utilize any such data to identify a fault classification identifier corresponding to the occurred fault and may select a predicted operational support data object associated with the fault classification identifier as an aid in resolving the fault corresponding to the identified fault classification identifier.

[0096] 4 illustrates another visualization of an exemplary support user interface for identifying and outputting at least one predicted operational support data object, according to at least some embodiments of the present disclosure. Specifically, FIG. 4 illustrates an exemplary support user interface 400. The exemplary support user interface 400 may be rendered on a client device during communication between the client device and the defect support apparatus 200, the client device communicating with the defect support apparatus 200 to access predicted operational support data object selection and provision functionality, and / or other support functionality. For example, the client device may render the support user interface 400 within a specially configured native application associated with the functionality of the defect support apparatus 200 and / or within a browser application utilized to access a web-based application associated with the functionality of the defect support apparatus 200.

[0097] The exemplary support user interface 400 includes a first sub-interface 402 associated with connecting and / or interacting with a technician to resolve the fault. For example, in some embodiments, the exemplary support user interface 400 is rendered on the client device during a support session initiation period (e.g., after a user requests to connect with a technician). In this regard, the first sub-interface 402 may show waiting messages, images, videos, and / or other content at the beginning while attempting to connect the client device with an appropriate technician device that may assist in diagnosing and / or resolving the particular identified fault. In some embodiments, once a technician device is identified and connected with the client device, the first sub-interface 402 may be dynamically updated to include a real-time communication interface (e.g., a chat interface) between the client device and the technician device. In some embodiments, the technician embodies a customer service representative. In this regard, the user may utilize the fault support session to convey specific text to the technician for processing, analysis, etc., to assist in resolving one or more faults associated with the network-connected device, the dynamic home communication network, etc. Additionally, at least a portion of the functionality (e.g., search functionality) may be provided before the problem support session is fully initiated. In some embodiments, the support session initiation period ends once a problem support session is established with a particular technician device or with a particular technician.

[0098] As illustrated, the first sub-interface 402 includes a search element 404. The search element 404 includes support search data 406 entered by a user. The support search data 406 may embody fault text description data indicating a particular fault to be resolved. In this regard, a user may enter the support search data 406 in an attempt to search for operational support data objects and / or initiate a connection with a technician device corresponding to a technician having sufficient capabilities to resolve the particular fault. In some embodiments, the support search data 406 is extracted and processed from the search element 404 to determine fault classification identifiers corresponding to faults indicated as affecting one or more network-connected devices and / or to select one or more predicted operational support data objects for output.

[0099] In some embodiments, the fault support apparatus 200 processes the support search data 406 to select one or more predicted operational support data objects for output. As illustrated, the support user interface 400 also includes a second sub-interface 352 that includes each of the operational support elements 354. In this regard, the fault support apparatus 200 may automatically, and in some embodiments dynamically, render the operational support elements in the second sub-interface 352 in the support user interface 400 in response to user input by a user of a client device. For example, in some embodiments, the fault support apparatus 200 receives the support search data 406 in real time upon submission of such input by a user, processes the support search data 406 to identify one or more fault classification identifiers, and / or in response to such input, output predicted operational support data objects for such fault classification identifiers in real time. In this regard, the user may interact with one or more of the predicted operational support data objects corresponding to the operational support elements 354 to attempt to resolve the fault while waiting for connection with the technician device. In some embodiments, an initiated connection with a technician device may subsequently be terminated, for example, upon provision of a predicted operational support data object determined to exceed a particular threshold of likelihood of resolving the fault associated with the fault classification identifier, upon receipt of user input associated with one or more of the predicted operational support resources represented by the operational support elements 354, upon receipt of user input indicative of a predicted operational support data object associated with the operational support elements 354 that will be assisted in resolving the fault, etc. In this regard, one or more such data determination conditions during a support session initiation period may simplify the establishment of a fault support session and terminate any such process that was initiated for initializing such a connection, searching for a technician or technician device, establishing a connection with a technician or technician device, etc.

[0100] In some embodiments, the support user interface is dynamically updated as the user interacts with the support user interface. For example, additional, updated fault text description data may be rendered in the support user interface as the user inputs such additional fault text description data. Additionally or alternatively, the predicted operational support data objects may be dynamically updated as such user input is received, e.g., in real-time or near real-time. For example, as additional fault text description data is received, the fault support apparatus 200 may select one or more updated predicted operational support data objects for output in real-time based at least on the additional fault text description data.

[0101] 5A and 5B illustrate visualizations of an exemplary dynamically updated support user interface for identifying and outputting at least one predicted operational support data object, according to at least some embodiments of the present disclosure. Specifically, FIGs. 5A and 5B illustrate dynamic updates of the exemplary support user interface 500 in response to updated fault text description data. It should be appreciated that the exemplary support user interface 500 may be dynamically updated any number of times, for example, whenever additional fault text description data is received by the fault support device 200 and / or upon selection of an updated operational support data object by the fault support device 200.

[0102] 5A shows an exemplary support user interface 500 in a first state before being dynamically updated. As illustrated, the exemplary support user interface 500 includes a first sub-interface 502. The first sub-interface 502 includes various interface elements associated with communications transmitted between the technician device and the client device during a fault support session. In this regard, during a fault support session, any number of message data objects, each of which embodies fault text description data, may be transmitted between the technician device and the client device. As illustrated, the first sub-interface 502 includes fault text description elements 504A and 504C transmitted via a technician device associated with the technician, and a fault text description element 504B transmitted by a client device associated with the user (collectively, all fault text description elements are referred to as "fault text description elements 504").

[0103] In some such embodiments, the defect support apparatus 200 may receive the defect text description data represented by each of the defect text description elements 504 as the defect text description elements 504 are entered via a client device and / or a technician device. Alternatively or additionally, in some embodiments, the defect support apparatus 200 may process the received defect text description data to select one or more predicted operational support data objects for output via an exemplary support user interface. For example, in some embodiments, the defect support apparatus 200 applies at least the defect text description data to an operational support processing data model that selects the predicted operational support data objects for output. In some such embodiments, as described herein, the operational support processing data model may generate a score that represents the likelihood that a particular operational support data object is associated with and / or otherwise assists in resolving a defect represented by one or more particular defect classification identifiers. Additionally or alternatively, the operational support processing data model may select predicted operational support data objects associated with such scores that meet a particular score threshold.

[0104] As illustrated, the exemplary support user interface 500 includes a second sub-interface 552. The second sub-interface 552 includes a first operational support element 554A associated with the first predicted operational support data object. The first predicted operational support data object may be selected as an operational support data object most likely to assist in resolving a fault indicated by and / or determined at least via fault text description data, e.g., a fault represented by a fault classification identifier determinable from at least a fault text description represented in the fault text description element 504. In some embodiments, the fault support apparatus 200 may score any number of possible operational support data objects and / or otherwise determine that the first predicted operational support data object associated with the first operational support element 554A is the only operational support data object associated with the score and meets an applicable score threshold.

[0105] 5B illustrates an exemplary support user interface according to a dynamically updated and / or subsequent second state, the second state being represented by an exemplary support user interface 510. As illustrated, the exemplary support user interface 510 includes a first sub-interface 502. The first sub-interface 502 reflects updated additional fault text description data represented by updated fault text description elements 506A and 506B. In this regard, the updated fault text description element 506A may embody updated fault text description data entered via a client device, for example, in response to a message embodying the fault text description data represented in the fault text description element 504C. Additionally or alternatively, the updated fault text description element 506A may embody additional fault text description data entered via a technician device, for example, in response to a message embodying the fault text description data represented in the fault text description element 506A.

[0106] The updated additional fault text description data may be processed to better identify the specific fault affecting the client device and / or the associated network-connected device. For example, fault text description element 506A indicates that the fault is affecting a printer having device characteristics that are brand identified by "Printer Brand A" and model identified by "Model 1." Such updated, updated fault text description data may be dynamically reflected via updates of first sub-interface 502 as it is entered via the client device and / or technician device, respectively.

[0107] As illustrated in the exemplary support user interface 510, the second sub-interface 552 similarly includes dynamic updates of interface elements represented in the second sub-interface 552. Specifically, as illustrated, the second sub-interface 552 includes interface elements associated with additional, updated operational support data objects. For example, the second sub-interface 552 includes a first additional updated operational support element 556A associated with the first additional updated operational support data object and a second additional updated operational support element 556B associated with the second additional updated operational support data object.

[0108] The defect support device 200 may select additional updated operational support data objects based at least in part on the additional updated defect support text data. For example, the defect support device 200 may receive additional updated defect text description data represented in the additional updated defect text description elements 506A and 506B and apply at least such additional updated defect text description data to the operational support processing data model. The operational support processing data model may, for example, select predicted operational support processing data objects having improved likelihoods associated with one or more identified defect classification identifiers and / or select one or more predicted operational support data objects based at least in part on the updated defect text description data to assist in resolving defects associated with the defect classification identifiers. In this regard, the operational support processing data model may select predicted operational support data objects corresponding to the updated operational support elements 556A and 556B. For example, the operational support processing data model may rescore any number of possible operational support data objects based at least in part on the updated additional defect text description data.

[0109] In some embodiments, the operational support elements corresponding to the selected predicted operational support data objects are rendered based at least in part on the scores and / or determinations associated with the predicted operational support data objects. For example, in some embodiments, the predicted operational support data objects are each scored by the operational support process data model, and then the support user interface is configured to render the predicted operational support data objects in descending order (e.g., starting with the highest-scoring predicted operational support data object). For example, as illustrated, the predicted operational support data object associated with the updated operational support element 556A may be scored higher than the predicted operational support data object associated with the operational support element 556B, which may be scored higher than the predicted operational support data object associated with the operational support element 554A. Additionally or alternatively, in some embodiments, the operational support elements may be rendered associated with only the highest-scoring predicted operational support data objects.

[0110] The second sub-interface 552 may be dynamically updated in any of a number of ways. In some embodiments, for example, the operational support elements associated with the previously output predicted operational support data objects may continue to be included in the second sub-interface 552. Alternatively or additionally, in some embodiments, the operational support elements associated with the previously output predicted operational support data objects may be replaced with the updated selected operational support data objects. For example, in some other embodiments, the operational support elements 554A may be replaced with additional updated predicted operational support data objects upon dynamic updating of the second sub-interface 552.

[0111] The support user interface may be dynamically updated on an ongoing basis as interactions occur through the support user interface. For example, as additional updated fault description text is entered associated with a fault support session, the selected predicted operational support data object may be updated based on such additional updated fault description text. In this regard, as additional context is made available via additional updated fault text description data, such additional context may be processed to identify more likely fault classification identifiers and / or to select updated predicted operational support data objects based on the additional context that are more likely to be useful in resolving the fault indicated by the context and / or associated fault classification identifier. Thus, the support user interface may be continually updated with interface elements associated with operational support data objects that are most likely to assist a user in diagnosing and / or resolving a fault indicated as affecting one or more network-connected devices.

[0112] The fault text description data (and / or other available data, such as device activity data, other support activity data, etc.) may be used to identify specific fault classification identifiers and / or associated predicted operational support data objects associated with a specific user profile and / or dynamic home communications network. In this regard, the fault text description data (alone or in combination with such other data) may be used to train an operational support processing data model to identify such relevant fault classification identifiers and / or associated predicted operational support data objects for selection. Thus, the fault text description data may serve as one such input to a trained model, such as an operational support processing data model, used to identify fault classification identifiers and / or predicted operational support data objects that are most likely to assist in resolving a fault associated with a user profile, such as a fault classification identifier that represents a specific fault indicated as affecting a network-connected device and / or dynamic home communications network associated with the user profile. 5B, for example, the fault text description data associated with fault text description element 504B may be processed with a higher weighting (e.g., via a data model) fault classification identifier and / or operational support data object associated with the printer problem and / or in combination with fault classification identifiers and / or operational support data objects of other input data (e.g., device activity data and / or other support activity data) associated with a particular printer that is currently active or was previously active on the dynamic home communication network associated with the user profile. Similarly, the fault text description data associated with fault text description element 504D may be further processed to refine such weighting, such as with a higher weighting fault classification identifier and / or operational support data object associated with a particular printer of printer brand A, model 1, alone or in combination with other input data.In this regard, it should be appreciated that as fault text description data is dynamically updated, the data model may be reapplied and / or otherwise subsequently executed to similarly dynamically update weights for particular fault support classification identifiers and / or predicted operational support data objects to reflect data that is best predicted to be associated with a particular user profile based, at least in part, on the newly entered fault text description data.

[0113] Exemplary Data Environment of the Present Disclosure Having described exemplary systems, devices, computing environments, and interfaces of the present disclosure, an exemplary data environment including visualizations of data elements and interactions between such data elements will now be described. It will be understood that the particular visualizations of data elements are exemplary, and that in some embodiments, data elements may actually be embodied using any of numerous data configurations, data types, and values. In this regard, the particular visualizations of data elements and interactions between such data elements are for non-limiting purposes of understanding, and are not intended to limit the scope and spirit of the disclosure herein and the appended claims.

[0114] 6 illustrates an example data representation of an operational support data object storage in an operational support management repository according to at least some embodiments of the present disclosure. Specifically, FIG. 6 illustrates an operational support management repository 602 configured to store any number of operational support data objects, such as each of operational support data objects 604A, 604B, 604C, 604D, and 604E (collectively, "operational support data objects 604"). In some embodiments, the operational support management repository 602 is embodied by, included in, and / or otherwise maintained by the defect support apparatus 200. Additionally or alternatively, in some embodiments, the operational support management repository 602 is embodied by, included in, and / or otherwise maintained by a separate device, system, and / or apparatus, and the defect support apparatus 200 is configured to access the operational support management repository 602. For example, in some such embodiments, the operational support management repository 602 may be maintained separately to enable periodic and / or ongoing updates of the operational support management repository 602 (e.g., adding new operational support data objects stored in the repository, purging old, unused, and / or otherwise marked operational support data objects previously stored in the repository, updating operational support data objects stored in the repository, etc.) without affecting the operation of the fault support apparatus 200.

[0115] The operational support management repository 602 may include one or more computing devices embodied in hardware, software, firmware, and / or combinations thereof. For example, the operational support management repository 602 may include one or more virtual databases, physical database servers, software-based storage solutions, etc. that store operational support data objects. The operational support management repository 602 may store any number of operational support data objects, each representing, for example, computer-executable instructions, software applications, web resources, and / or other content that assists in resolving one or more faults.

[0116] In some embodiments, the operational support management repository 602 stores third-party defect support data objects. Each third-party operational support data object may embody a data link (e.g., a URL, an IP address, etc.) or other data drive mechanism for accessing data objects stored by devices, systems, and / or other computing devices external to the operational support management repository 602 and / or the defect support apparatus 200. In this regard, the third-party operational support data object may enable access to other data objects stored by external data systems. Each third-party operational support data object may be maintained by a different external system and / or associated with a different provider entity that controls the data system that stores the data object retrieved via the third-party operational support data object. For example, two different third-party operational support data objects may be associated with the same provider entity but accessible via different external systems associated with the same provider entity. Alternatively or additionally, two different third-party operational support data objects may be associated with different provider entities and accessible via different external systems. Further, additionally or alternatively, in some embodiments, operational support management repository 602 stores operational support data objects that do not require access via external data systems (e.g., files, internal links, and / or other resources embodying content stored in operational support management repository 602). In this regard, operational support management repository 602 advantageously provides a centralized mechanism for enabling access to operational support data objects, regardless of whether data corresponding to such operational support data objects is stored locally or maintained externally.

[0117] As illustrated, each of the operational support data objects 604 embodies data links to data objects associated with resolving one or more faults. The various operational support data objects 604 are associated with various provider identifiers, specifically provider identifiers representing providers 1, 2, 3, and 4. Each of the providers may maintain any number of systems for storing and / or otherwise making accessible data associated with one or more operational support data objects. In some embodiments, one or more of the provider identifiers correspond to an entity that controls the operational support management repository 602 and / or the fault support apparatus 200. Alternatively or additionally, in some embodiments, each of the provider identifiers corresponds to a third party entity that controls one or more data systems external to the operational support management repository 602 and / or the fault support apparatus 200. As shown, operational support data object 604A and operational support data object 604B are each associated with provider 1, operational support data object 604C is associated with provider 2, operational support data object 604D is associated with provider 3, and operational support data object 604E is associated with provider 4.

[0118] Operations support data object 604A embodies a first third party operations support data object associated with web content hosted by Provider 1. For example, the third party operations support data object embodies a web page 606A hosted by an external system controlled by Provider 1. The web page includes a variety of content, including textual content associated with connecting a printer to a home network. In this regard, the third party operations support data object stored in operations support management repository 602 may embody a URL utilized to retrieve the web page from the external system hosting the web page.

[0119] The operational support data object 604E embodies a second third-party operational support data object associated with the web content hosted by Provider 4. For example, the third-party operational support data object embodies a web page 606B hosted by an external system controlled by Provider 4. The web page includes various content, including textual content associated with determining why a computing device's battery may consistently appear to be depleted. In this regard, it should be appreciated that the third-party operational support data object stored in the operational support management repository 602 may embody a URL utilized to retrieve the web page from the external system hosting the web page. In a situation where the identified fault classification identifier represents a printer fault, the operational support data object 604A may be output and utilized to access the corresponding data (e.g., web page 606A). Similarly, in a situation where the identified fault classification identifier represents a battery life fault, the operational support data object 604E may be output and utilized to access the corresponding data (e.g., web page 606B). For example, an operational support processing data model may be trained to identify fault classification identifiers indicated by data associated with a particular set of devices, communication networks, and / or user profiles (e.g., device activity data, support activity data, fault text description data, etc.).

[0120] It will be appreciated that in some embodiments, the operational support data objects stored in the operational support management repository 602 include one or more third-party operational support data objects having content stored outside of the operational support management repository 602. In some such embodiments, the operational support data objects stored in the operational support management repository 602 embody data pointers that can be used to retrieve such content and / or associated context from an external location (e.g., another database, server, etc.). In some such embodiments, content pointed to by a third-party operational support data object may be updated without requiring an update of the corresponding third-party operational support data object. In this regard, such embodiments utilize third-party operational support data objects to reduce the storage requirements of the operational support management repository 602 (e.g., by reducing the need to store content in the operational support management repository 602 that is often significantly more resource intensive than data pointers) and to reduce or eliminate the need to update the operational support management repository 602 to update content pointed to by a particular third-party operational support data object.

[0121] FIG. 7 illustrates an example data representation of an operational support data object associated with a defect classification identifier, according to at least some embodiments of the present disclosure. In some embodiments, the association between the defect classification identifier and the operational support data object is maintained by the defect support device 200. For example, in some embodiments, the association between the defect classification identifier and the operational support data object is stored in an operational support management repository. For example, each operational support data object may be embodied by one or more data records stored in the operational support management repository that include the defect classification identifier with which the operational support data object is associated. Alternatively or additionally, in some embodiments, the association between the operational support data object and the defect classification identifier is maintained by the defect support device 200 and / or stored in one or more other repositories accessible to the defect support device 200.

[0122] 7 illustrates an association between operational support data objects 604 and various fault classification identifiers 702A, 702B, 702C, and 702D. Fault classification identifier 702A represents a classification of a system event that embodies a fault in connecting a new device to a communications network (e.g., a home network). Fault classification identifier 702B represents a classification of a system event that embodies a fault in the operation of a printer having a make of printer brand A. Fault classification identifier 702C represents a classification of a system event that embodies a fault in the printer generally.

[0123] The fault classification identifier 702D represents a classification system event that embodies a fault that results in a reduction in device battery life. It should be understood that the first fault classification identifier may represent a more detailed and / or narrower classification of the fault represented by the second fault classification identifier. For example, a "printer problem" may encompass all the various faults for various types, makes, and / or models of printers, a "Brand A Printer Problem" may encompass a subset of such faults that are specific to printers having a brand of printer brand A, and similarly, a fault classification identifier for a "Brand A Model 1 Printer Problem" may encompass a subset of faults of the fault classification identifier "Brand A Printer Problem", specifically, faults associated with model 1 of the Brand A printer. Thus, fault classification identifiers may be generated to represent any level of specificity and / or detail with respect to device characteristics, data characteristics, and the like. The fault classification identifier 702D represents a classification system event that embodies a fault that results in a reduction in device battery life.

[0124] In some embodiments, each association between an operations support data object and a fault classification identifier indicates that the operations support data object assists in resolving one or more faults represented by the fault classification identifier. For example, as shown, operations support data object 604A is associated with fault classification identifiers 702A, 702B, and 702C. In this regard, the association with fault classification identifier 702A indicates that operations support data object 604A may assist in resolving a fault involving the connection of a new network-connected device, the association with fault classification identifier 702B indicates that operations support data object 604A may assist in resolving a fault involving a printer having a make of brand A, and the association with fault classification 702C indicates that operations support data object 604A may assist in resolving faults involving printers in general. Alternatively, operational support data object 604B is associated with fault classification identifier 702B and fault classification identifier 702C, indicating that operational support data object 604B may similarly assist in resolving faults involving a printer having a brand A make and / or involving printers in general but not involving the connection of a new network-connected device (e.g., no association is established with fault classification identifier 702A).

[0125] Furthermore, operational support data objects 604C and 604D are each associated only with fault classification identifier 702C. Such an association may indicate that operational support data objects 604C and 604D may each assist in resolving faults generally involving printers, but not specific to printers having a brand A make, and / or in resolving faults involving the attachment of a new device. For example, operational support data object 604C may be associated with or otherwise include text data, software applications, video content data, image content data, etc., that assist in resolving faults associated with a printer cartridge for an inkjet printer. Similarly, operational support data object 604D may be associated with or otherwise include text data, software applications, video content data, image content data, etc., that assist in resolving faults associated with the operation of a printhead for a thermal printer.

[0126] Finally, the operational support data object 604E is associated only with the fault classification identifier 702D. Such an association indicates that the operational support data object 604E may assist in resolving faults involving reduced battery life of a network-connected device. In this regard, the operational support data object 604E may not assist in resolving any faults represented by one or more of the other fault classification identifiers 702A, 702B, and / or 702C. For example, the operational support data object 604E may be associated with or otherwise include text data, software applications, video content data, image content data, etc. that assist in resolving faults associated with degraded and / or otherwise reduced battery life (e.g., diagnosing hardware thermal fatigue issues, software applications that drain significant battery life, etc.).

[0127] Such associations between operational support data objects and one or more defect classification identifiers may be generated manually and / or automatically based at least in part on processing of the operational support data objects and / or defect classification identifiers. For example, in some embodiments, a database administrator of a repository in which such associations are stored (e.g., a database administrator of an operational support management repository) may generate and / or store such associations based on the content of the operational support data objects. Alternatively or additionally, in some embodiments, the defect support apparatus 200 processes content, metadata, and / or any other data associated with the operational support data objects to generate associations between the operational support data objects and one or more defect classification identifiers. For example, in some embodiments, the defect support apparatus 200 may utilize natural language processing to determine which defects are discussed in the content data of a particular operational support data object. The defect support apparatus 200 may associate operational support data objects with defect classification identifiers that represent defects identified in such content data.

[0128] In some such embodiments, the defect support apparatus 200 associates the operational support data object with a defect classification identifier that represents a defect identified in such content data. In some embodiments, text processing, pattern recognition, image recognition, and / or any other algorithms for processing the content of the operational support data object are utilized to generate a defect classification identifier associated with the operational support data object and / or associate the operational support data object with an existing defect classification identifier. For example, in some embodiments, the operational support data object may be processed to determine the most prominent topics, defects, devices, device types, or other category groups, etc., mentioned in the content of the operational support data object. In some such embodiments, the operational support data object is associated with the determined defect classification identifier associated with the determined topic, defect, device, device type, or other category group, etc.

[0129] 8 illustrates an example visualization of predicted operational resource selection utilizing an operations support process data model, according to at least some embodiments of the present disclosure. Specifically, FIG. 8 illustrates an example operations support process data model 808 that selects and / or outputs at least predicted operations support data objects 810 based on one or more input portions of data. In this regard, the fault support apparatus 200 may maintain the operations support process data model 808 to select the predicted operations support data objects 810. The operations support process data model 808 may be pre-trained based on the particular type of input data utilized to select the operations support data objects.

[0130] The operations support process data model 808 may be embodied in any of a number of manners. For example, in some embodiments, the operations support process data model 808 is embodied by one or more specially configured and / or trained algorithmic models, statistical models, and / or machine learning models, or a combination thereof. The operations support process data model 808 may be configured and / or trained using supervised learning and / or unsupervised learning. For example, in some embodiments, the operations support process data model 808 is embodied by one or more regression models, random forest models, KNN models, etc. In some embodiments, the operations support process data model 808 is embodied by one or more k-means models, clustering models, etc. In some embodiments, the operations support process data model 808 embodies artificial intelligence specially configured to select predicted operations support data objects 810 based at least in part on input data.

[0131] As illustrated, the operational support processing data model 808 takes as input at least a device activity data set 802. In some embodiments, the device activity data 802 includes various data received, requested, and / or otherwise detected for one or more network-connected devices, communication networks, and / or requesting client devices that are processed to provide predicted operational data objects associated with identified malfunctions. Such device activity data 802 may include, without limitation, one or more configuration logs, device identification data, connections between devices, and the like, associated with such network-connected devices, communication networks, client devices, and the like. In this regard, the device activity data 802 may include various data related to identifying a particular computing device, data characteristics of such computing devices, and the like. Additionally or alternatively, in some embodiments, the device activity data 802 may include various data indicative of a current configuration of such computing devices, and / or changes in the configuration of computing devices.

[0132] In some embodiments, the device activity data 802 is received from the defect support apparatus 200 for processing. The device activity data 802 may be received from a requesting client device that collects a portion of the device activity data from each network-connected device capable of communicating with the requesting client device over one or more communication networks at any number of time intervals. Alternatively or additionally, in some embodiments, the defect support apparatus 200 requests the device activity data directly from the requesting client device and / or one or more network-connected devices. The defect support apparatus 200 may request the device activity data 802 upon initiation of a defect support session, at regular time intervals, upon receipt of other input data (e.g., defect text description data), etc. Alternatively or additionally, in some embodiments, the defect support apparatus 200 detects the device activity data. For example, the defect support apparatus 200 may process transmission messages, networking packets, and / or other data conveyed over a particular communication network to determine the device activity data 802 from metadata and / or data therein. In some embodiments, device activity data is collected and / or requested by fault support apparatus 200 over a particular timestamp interval. For example, at the start of a process for selecting predicted operational support data objects, fault support apparatus 200 may request and / or otherwise retrieve (e.g., from a buffer of stored device activity data) device activity for one or more network-connected devices over a predefined timestamp interval (e.g., the last day, hour, etc.).

[0133] As illustrated, optionally, in some embodiments, the operational support process data model 808 additionally or alternatively takes as input at least support activity data 804. In some embodiments, the support activity data 804 includes various data associated with actions performed by a user to diagnose and / or attempt to resolve one or more faults. Such support activity data 804 may include, but is not limited to, support search data performed via one or more network-connected devices, fault text description data, previously accessed operational support data objects, and / or external query data. In this regard, the support activity data 804 may include various data related to specific support-related actions performed by a user to diagnose and / or attempt to resolve one or more faults. In some embodiments, the operational support process data model 808 is utilized in addition to and / or in lieu of one or more other processes that identify, manually or via another automated computer-implemented process, specific faults, corresponding predicted operational support data objects, and / or the like.

[0134] In some embodiments, the support activity data 804 is received by the defect support apparatus 200 for processing. The support activity data 804 may be received from a requesting client device in response to a request by the defect support apparatus 200. In some embodiments, the defect support apparatus 200 requests the support activity data 804 at specific time intervals and / or upon determination of the occurrence of a specific event. For example, in some embodiments, the defect support apparatus 200 requests the support activity data 804 from a requesting client device and / or associated network-connected device in response to receiving data requesting and / or triggering the initiation of a defect support session. Alternatively or additionally, in some embodiments, the defect support apparatus 200 receives and stores some or all of the support activity data 804 as the requesting client device interacts with the defect support apparatus 200. For example, the defect support apparatus 200 may receive and store the support activity data 804 including defect text description data entered via the requesting client device and / or associated network-connected device during a main support process, such as a defect support session. Alternatively or additionally, in some embodiments, for example, the problem support apparatus 200 receives and stores support search data by a requesting client device indicative of a user request to initiate a problem support session.

[0135] Additionally or alternatively, optionally, in some embodiments, the operations support process data model 808 takes as input at least an operations support data object set 806. The operations support data object set 806 may embody a set including any number of operations support data objects available for selection by the operations support process data model 808. In some embodiments, the defect support apparatus 200 retrieves the operations support data object set 806 from an operations support management repository. The operations support data object set 806 may include all available operations support data objects, or in some embodiments, may include a particular subset of available operations support data objects. For example, in some embodiments, a defect classification identifier is identified prior to processing by the operations support process data model 808, and the operations support data object set 806 may include a subset of available operations support data objects associated with the identified defect classification identifier.

[0136] As illustrated, optionally, in some embodiments, operational support process data model 808 additionally or alternatively takes as input at least support activity data 804. In some embodiments, support activity data 804 includes various data associated with actions performed by users to attempt to diagnose and / or resolve one or more faults. Such support activity data 804 may include, but is not limited to, support search data performed via one or more network-connected devices, fault text description data, previously accessed operational support data objects, and / or external query data. In this regard, support activity data 804 may include various data related to specific support-related actions performed by users to attempt to diagnose and / or resolve one or more faults.

[0137] In some embodiments, the support activity data 804 is received by the defect support apparatus 200 for processing. The support activity data 804 may be received from a requesting client device in response to a request by the defect support apparatus 200. In some embodiments, the defect support apparatus 200 requests the support activity data 804 at specific time intervals and / or upon determination of the occurrence of a specific event. For example, in some embodiments, the defect support apparatus 200 requests the support activity data 804 from a requesting client device and / or associated network-connected device in response to receiving data requesting and / or triggering the initiation of a defect support session. Alternatively or additionally, in some embodiments, the defect support apparatus 200 receives and stores some or all of the support activity data 804 as the requesting client device interacts with the defect support apparatus 200. For example, the defect support apparatus 200 may receive and store the support activity data 804 including defect text description data entered via the requesting client device and / or associated network-connected device during a main support process, such as a defect support session. Alternatively or additionally, in some embodiments, for example, the problem support apparatus 200 receives and stores support search data by a requesting client device indicative of a user request to initiate a problem support session.

[0138] It should be appreciated that the operations support process data model 808 may be trained with and / or take as input any additional and / or alternative data relevant to determining predicted operations support data objects most likely to assist a user in resolving one or more faults. In this regard, the operations support process data model 808 may be trained with and / or take as input any data related to a particular communications network and / or network connected device, support actions performed associated with this data, external system data associated with a particular device and / or fault, etc. For example, the operations support process data model 808 may be trained based at least in part on social media data, web articles, blog posts, etc., that indicate particular faults that generally affect a particular device, device type, etc.

[0139] In some embodiments, the operations support process data model 808 outputs predicted operations support data objects 810 based at least in part on the input data. The predicted operations support data objects 810 may embody operations support data objects that are determined to be sufficiently likely to assist in resolving the fault associated with the identified fault classification identifier. In this regard, the predicted operations support data objects 810 may each be output to enable access to the operations support data object and / or content in the operations support data object for use in attempting to resolve the fault (e.g., automatically or via a user-initiated action based at least in part on one or more of the predicted operations support data objects 810).

[0140] In some embodiments, the operations support processing data model 808 generates a confidence score for one or more operations support data objects (e.g., each operations support data object in the operations support data object set 806). The confidence score for each operations support data object may represent a likelihood associated with the operations support data object attempting to resolve a particular identified fault classification identifier. For example, in some embodiments, the operations support processing data model 808 processes some or all of the input data (e.g., the device activity data 802 and / or the support activity data 804) to identify fault classification identifiers representing one or more faults affecting network-connected devices that can communicate with and / or are otherwise associated with a particular requesting client device. Alternatively or additionally, in some embodiments, the operations support processing data model 808 receives the identified fault classification identifiers as input. Thus, the generated confidence score for each operations support data object may embody a likelihood and / or confidence that the fault support apparatus 200 has that the operations support data object will assist in resolving the fault associated with the identified fault classification identifier.

[0141] In some embodiments, the operations support process data model 808 selects predicted operations support data objects 810 based on a confidence score for each operations support data object. For example, in some embodiments, the operations support process data model 808 is configured to select and output a determinable number of predicted operations support data objects 810 that are associated with the highest confidence scores. For example, in some embodiments, other determinable numbers of operations support data objects having the top 1, top 3, top 10%, and / or highest confidence scores are selected and / or output. Alternatively or additionally, in some embodiments, the operations support process data model 808 selects and / or outputs predicted operations support data objects 810 that embody all operations support data objects that meet a certain minimum score threshold. In some such embodiments, any number of predicted operations support data objects may be identified based on scores (e.g., confidence scores) generated by the operations support process data model 808.

[0142] The predicted operational support data objects may be utilized in any of a number of manners. In some embodiments, the fault support apparatus 200 outputs the predicted operational support data objects 810 to a requesting client device. The requesting client device may render the predicted operational support data objects 810 via a support user interface. In some such embodiments, a user of the requesting client device may analyze the predicted operational support data objects 810 rendered by the requesting client device and determine whether to interact with any of the predicted operational support data objects. In the event of interacting with one or more of the predicted operational support data objects 810, the main support process (e.g., the fault support session) may be interrupted and / or terminated. Alternatively or additionally, in some embodiments, a user input may be received indicating one or more accessed data objects of the predicted operational support data objects 810 that assist in resolving one or more faults, and the fault support apparatus 200 may terminate the main support process in response to receiving such an indication.

[0143] In some embodiments, the operational support processing data model 808 outputs a fault classification identifier 812. The fault classification identifier 812 may represent one or more faults associated with the requesting client device, the network-connected devices capable of communicating with the requesting client device, and / or the communication network. In some embodiments, the operational support processing data model 808 is configured to select the fault classification identifier from one or more portions of the input data. For example, in some embodiments, the operational support processing data model 808 is configured to select the fault classification identifier 812 based at least in part on the device activity data 802 and / or the support activity data 804. In one such exemplary context, the fault support apparatus 200 may determine a fault indicated as affecting one or more network-connected devices based on the support activity data 804 (e.g., from fault text description data embodied in the support activity data 804) and may identify a network-connected device corresponding to such fault based at least in part on the device activity data 802. In this regard, in some embodiments, the operational support process data model 808 scores each possible fault classification identifier and selects and outputs the fault classification identifier 812 associated with the highest score.

[0144] It should be appreciated that in other embodiments, the operations support process data model 808 includes one or more sub-models. For example, in some embodiments, the operations support process data model 808 includes a first sub-model that is specifically configured and / or trained to select predicted operations support data objects 810 and a second sub-model that is specifically configured and / or trained to select fault classification identifiers 812. Alternatively or additionally, in some embodiments, a second model, separate from the operations support process data model 808, is specifically configured and / or trained to select fault classification identifiers 812.

[0145] In some embodiments, the operational support process data model 808 is trained to identify certain trends, patterns, and / or other relationships between the faults represented by the fault classification identifiers. For example, in some embodiments, the operational support process data model determines causal relationships between such faults, such that resolving a causal fault resolves one or more other faults. In some such embodiments, the operational support process data model 808 determines such causal relationships based at least in part on patterns, trends, and / or other relationships determined from various training data sets. For example, the device activity data and / or the support activity data may include data indicating that when a particular fault is indicated, one or more other faults are frequently or always indicated as well. A non-limiting example of a causal fault (e.g., a fault that causes one or more other faults) is an improperly configured network access point that blocks connections from network-connected devices that access a particular port range. In this regard, the device activity data may indicate attempts to connect and / or configure individual network-connected devices to access a particular port range, and thus, may indicate such additional faults (e.g., connectivity problems for individual devices). In this regard, the operations support process data model may identify and / or associate a causative failure with one or more additional failures that are indicated by the input training data as occurring together (e.g., in a daisy chain or otherwise simultaneous effect). The operations support process data model 808 may then be trained to identify the causative failure and higher weighted operations support data objects associated with resolving such causative failure.

[0146] It should be further appreciated that the operational support process data model 808 may be trained based on (and / or take as input any of) any of a number of types of training data sets, including additional data not shown that is additional to and / or associated with the device activity data 802 and / or the support activity data 804, and may be trained for any of a number of target objectives. For example, in some embodiments, the operational support process data model 808 is trained based at least in part on device identification data that uniquely identifies network-connected devices of a communication network (e.g., a dynamic home communication network). Alternatively or additionally, in some embodiments, the operational support process data model 808 may be trained at least in part on data embodying past fault classification identifiers that have affected a particular communication network and / or a network-connected device on a particular communication network. In this regard, the past fault classification identifiers may be associated with other specific data (e.g., device activity data, support activity data, etc.) that are indicative of the presence of a fault represented by the past fault classification identifier. Additionally or alternatively, in some embodiments, the operational support processing data model 808 may be trained based at least in part on aggregate data collected for multiple communication networks in general, and / or multiple communication networks determined to be similar to a particular home communication network (e.g., a data model trained at least in part on data associated with another dynamic home communication network including a similar type of network-connected devices, a similar number of network-connected devices, a similar topology of network-connected devices, etc.). Further, alternatively or additionally, in some embodiments, the operational support processing data model 808 may be trained at least in part on data provided by the network-connected device equipment manufacturer (e.g., device OEM data indicating the presence of a particular malfunction based on received data and / or operational data).In this regard, embodiments of the present disclosure may access any of a number of available data repositories internal and / or external to the fault support apparatus 200 to retrieve, for example, data (e.g., device activity data, support activity data, past fault classification identifiers, etc., for faults affecting particular network-connected devices and / or communications networks) used to train the operational support process data model 808. By accessing such a range of available data, a particular operational support process data model 808 may be trained based on any relevant portions of such data to maximize accuracy with respect to a particular target objective (e.g., maximize the likelihood that a predicted operational support data object will be selected that will assist in resolving a fault identified as affecting or likely to affect a network-connected device and / or communications network).

[0147] Additionally or alternatively, it should be appreciated that the operations support process data model 808 may be trained utilizing data associated with numerous different communication networks, network-attached devices of the communication networks, and the like. For example, in some embodiments, the operations support process data model 808 is trained based on a training dataset and includes device activity data, support activity data, and / or other data specific to the network-attached devices of one particular communication network. In this regard, the operations support process data model 808 may be trained to perform particular determinations, detect particular trends, and / or otherwise learn particular aspects of one communication network (e.g., which data indicates a particular fault classification identifier, which operations support data objects are to be selected based on the particular data, etc.). Alternatively or additionally, in some embodiments, the operations support process data model 808 is trained based on a training dataset that includes data associated with multiple communication networks. In this regard, the operational support processing data model 808 may be trained to perform particular decisions, detect particular trends, and / or otherwise generally learn from the data associated with each communication network (e.g., to identify trends across all data sets and / or to learn some individual trends associated with each communication network). Similarly, embodiments may specifically select a corpus of training data sets that best enables configuring the operational support processing data model 808 for a particular target objective (e.g., user profile specific operational support data object selection, general operational support data object selection based on training data associated with all available communication networks, etc.).

[0148] Exemplary Processes of the Present Disclosure Having described the exemplary systems, apparatus, computing environments, interfaces, and data visualizations of the present disclosure, an exemplary process according to the present disclosure will now be described. It will be understood that each of the flowcharts illustrates an exemplary computer-implemented process that may be executed by one or more of the apparatus, systems, devices, and / or computer program products described herein, for example, utilizing one or more of its specially configured components.

[0149] The illustrated blocks indicate the operations of each process. Such operations may be in any of numerous ways, including, but not limited to, in the order and manner as shown and described herein. In some embodiments, one or more blocks of any of the processes described herein are performed between one or more blocks of another process, before one or more blocks of another process, in parallel with one or more blocks of another process, and / or as a sub-process of a second process. Additionally or alternatively, any of the processes may include some or all of the operational steps described and / or shown, including one or more optional blocks, in some embodiments. With respect to the flowcharts shown herein, one or more of the illustrated blocks may be optional in some or all embodiments of the present disclosure. Optional blocks are indicated with dashed lines (or "dotted lines"). Similarly, it should be understood that one or more of the operations of each flowchart may be combined, interchangeable, and / or otherwise modified as described herein.

[0150] FIG. 9 illustrates a flow chart showing an example operation of an example process for applying device activity data and fault text description data to an operational support processing data model to select predicted operational support data objects for output, according to at least some example embodiments of the present disclosure. Specifically, FIG. 9 illustrates the operation of an example process 900. In some embodiments, the process 900 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 900 is executed by one or more specially configured computing devices, such as the fault support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the fault support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in the fault support apparatus 200, for example, in the memory 204 and / or another component shown and / or described herein, and / or otherwise accessible to the fault support apparatus 200, to perform the operations as described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatuses, systems, devices, etc. to perform one or more of the operations as shown and described. For example, the fault support apparatus 200 may communicate with a client device and / or an external data system. For purposes of simplicity of explanation, the process 900 is described as being performed by and from the perspective of the fault support apparatus 200.

[0151] The process 900 begins at optional operation 902. At optional operation 902, the defect support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for receiving user input by a requesting client device requesting initiation of a defect support session. The user input requesting initiation of a defect support session may embody and / or include one or more pieces of data indicating that a user has submitted an explicit request to initiate a defect support session and / or other data that may be utilized to initiate a defect support session. For example, in some embodiments, the user input includes a user submission, such as support search data and / or other defect text description data.

[0152] At operation 904, the defect support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for initiating a defect support session associated with the requesting client device. In some embodiments, the defect support session is initiated associated with the original requesting client device from which user input was received in a previous step (e.g., at optional operation 902) requesting initiation of the defect support session. In some embodiments, the defect support apparatus 200 initiates the defect support session and initiates an attempt to connect the requesting client device with a technician device. Additionally or alternatively, in some embodiments, initiating the defect support session may include connecting the requesting client device to an automated support platform that facilitates information gathering and / or communication with the requesting client device, and / or otherwise granting the requesting client device access to the automated support platform. For example, in some embodiments, the automated support platform includes or embodies an automated chatbot, artificial intelligence, etc. that transmits message data objects to and / or receives message data objects from the requesting client device.

[0153] In some embodiments, initiating a problem support session includes initiating a process for establishing a connection between the requesting client device and a technician device associated with the technician. For example, in some embodiments, the problem support apparatus selects a technician from a set of available technicians. In some embodiments, the technician is selected at least in part based on any of a number of parameters, including but not limited to, based at least in part on availability, technical expertise, workload, etc. Once a technician is selected, a connection between the requesting client device and the technician device corresponding to the technician may be established after a predefined delay or immediately upon determining that a minimum time has elapsed since initiating the process for establishing the connection (e.g., after a determinable minimum number of seconds). In some embodiments, the connection is established directly between the requesting client device and the technician device (e.g., in a peer-to-peer manner or in a client-server manner with the requesting client device and the technician device as a server). Alternatively or additionally, in some embodiments, the connection is established indirectly between the requesting client device and the technician device (e.g., using the problem support apparatus 200 as an intermediary for transmitting data between the connected devices).

[0154] In some embodiments, upon initiation of a fault support session associated with a requesting client device, the fault support apparatus 200 begins retrieving and / or collecting device activity data and / or support activity data associated with the requesting client device and / or network-connected devices and / or communication networks associated with the network-connected devices. For example, in some embodiments, the fault support apparatus 200 retrieves and / or collects device activity data corresponding to network-connected devices and / or communication networks associated with a user profile linked to the requesting client device. Alternatively or additionally, in some embodiments, the fault support apparatus 200 retrieves and / or collects device activity data corresponding to network-connected devices and / or communication networks to which the requesting client device is connected and / or otherwise capable of communication. The device activity data may be retrieved from a device activity data repository maintained by the fault support apparatus 200, requested from and received in response to the requesting client device, detected directly via communication with a communication network, and / or detected indirectly utilizing the requesting client device to communicate with a particular communication network and / or network-connected device. In some embodiments, for example, a requesting client device and / or one or more other network-connected devices are configured to provide device activity data to fault support apparatus 200 at particular times, upon the occurrence of a particular trigger event, and / or other determinable circumstances.

[0155] The defect support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for correlating the device activity data and the defect text description data to the defect support session in operation 906. In some embodiments, the defect text description data is received via the defect support session. Alternatively or additionally, in some embodiments, the defect text description data is received in response to one or more operations performed by the requesting client device and / or another associated device. For example, in some embodiments, the defect text description data is received embodying or in conjunction with a user input requesting the initiation of a defect support session and / or during an initiated defect support session.

[0156] The defect support device 200 includes means, such as a support providing circuit 210, a communication circuit 208, an input / output circuit 206, a processor 202, etc., or a combination thereof, for applying the device activity data and the defect text description data to an operational support processing data model in real time in operation 908 to select predicted operational support data objects from the operational support management repository.

[0157] In some embodiments, the fault support apparatus 200 maintains an operations support management repository to include any number of operations support data objects. In some such embodiments, the operations support management repository includes data enabling access to one or more externally stored third-party operations support data objects. For example, the operations support management repository may include links to third-party operations support data objects each embodying a web resource hosted on a third-party server. In some embodiments, the operations support management repository may be maintained manually (e.g., by one or more database administrators associated with the fault support apparatus 200) such that a user may manually store new operations support data objects in the operations support management repository, delete operations support data objects from the operations support management repository, and / or otherwise configure the operations support data objects stored in the operations support management repository. Additionally or alternatively, in some embodiments, the operations support management repository is maintained automatically. For example, the fault support apparatus 200 may identify and / or process available internal and / or external data objects, determine whether such resources satisfy one or more applicable conditions for storage as operational support data objects (e.g., whether the content of the data object is associated with resolving the fault), and store the data object as an operational support data object if the applicable conditions are determined to be satisfied. For example, some embodiments parse, extract, and / or process content data of a particular resource, metadata associated with the resource, and / or the like, or a combination thereof, to automatically generate a corresponding operational support data object based at least in part on such data. Some such embodiments perform automated processing to determine whether a resource is determined to resolve or assist in resolving a particular fault, and / or fault classification identifiers, or other data that are utilized to store and / or enable retrieval of the resource with the corresponding fault.In some other embodiments, a separate associated operational support management system updates an operational support management repository that is separate from the fault support apparatus 200 .

[0158] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for outputting the predicted operational support data object to the requesting client device in real time at operation 910. In some embodiments, the fault support apparatus 200 transmits the predicted operational support data object to the requesting client device by one or more data transmissions. The fault support apparatus 200 may transmit the predicted operational support data object to cause the requesting client device to render in real time a support user interface including at least an interface element associated with the predicted operational support data object. In this regard, the predicted operational support data object may be rendered by the client device early enough to allow the predicted operational support data object to be accessed during the initiation of a fault support session, before the fault support session connects the requesting client device with a technician device, and / or during communication between the requesting client device and the technician device as part of the fault support session. Alternatively or additionally, in some embodiments, the fault support apparatus 200 outputs the predicted operational support data objects, for example, via transmission of an external message.

[0159] FIG. 10 illustrates a flow chart showing an example operation of an example process for terminating an initiation of a fault support session, according to at least some example embodiments of the present disclosure. Specifically, FIG. 10 illustrates the operation of an example process 1000. In some embodiments, the process 1000 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 1000 is executed by one or more specially configured computing devices, such as the fault support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the fault support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in the fault support apparatus 200, for example, in the memory 204 and / or in another component shown and / or described herein, and / or otherwise accessible to the fault support apparatus 200, to perform the operations as described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatus, systems, devices, etc. to perform one or more of the operations as shown and described. For purposes of simplicity of explanation, the process 1000 is described as being performed by and from the perspective of the fault support apparatus 200.

[0160] Process 1000 begins at operation 1002. In some embodiments, process 1000 begins after one or more operations shown and / or described with respect to any of the other processes described herein. For example, in some embodiments as described, process 1000 begins after execution of operation 910. In this regard, some or all of process 1000 may replace or complement one or more blocks shown and / or described with respect to any of the other processes described herein. Upon completion of process 1000, the flow of operations may end. Additionally or alternatively, as shown, upon completion of process 1000, the flow may return to one or more operations of another process. It should be understood that in some embodiments, process 1000 embodies a sub-process of one or more other processes, such as process 900.

[0161] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for receiving user input by a requesting client device engaging an operational support data object at operation 1002. In some embodiments, for example, user interaction via the requesting client device engages an interface element corresponding to the operational support data object. The resulting user input is transmitted from the requesting client device in response to such user engagement indicative of user engagement with and / or access to the predicted operational support data object. For example, in some embodiments, a user of the requesting client device may click and / or otherwise engage with a predicted operational support data object in circumstances where the user determines that the predicted operational support data object is likely to enable the user to resolve a particular fault affecting one or more network-connected devices accessible to the user.

[0162] The defect support apparatus 200 includes means, such as the support providing circuit 210, the communication circuit 208, the input / output circuit 206, the processor 202, etc., or a combination thereof, for terminating the initiation of a defect support session in response to receiving a user input involving an operational support data object in operation 1004. The defect support apparatus 200 may terminate the defect support session in response to receiving a user input involving an operational support data object, since such user input may indicate an intention to resolve one or more defects using the predicted operational support data object instead of using the technical support received via the defect support session. In some embodiments, the defect support apparatus 200 terminates searching for a technician device to connect with the requesting client device and / or terminates a pending connection between the requesting client device and the technician device. In a situation where a defect support session has already been initiated, the defect support apparatus 200 may terminate the defect support session.

[0163] In some embodiments, terminating the initiation of a problem support session includes terminating one or more sub-processes and / or data connections. For example, in some embodiments, the problem support apparatus 200 terminates a process for establishing a connection between the requesting client device and the technician device. Alternatively or additionally, in some embodiments, the problem support apparatus terminates a process for searching for a technician to connect the requesting client device. In some contexts, such as when a problem support session has already been initiated and / or when a connection between the requesting client device and the technician device has been established, the problem support apparatus 200 may terminate the problem support session and / or the connection between the devices. In such embodiments, the problem support apparatus 200 saves processing resources that would otherwise be consumed to establish and / or maintain the problem support session.

[0164] FIG. 11 illustrates a flow chart showing an example operation of an example process for dynamically outputting updated predicted operational support data objects according to at least some example embodiments of the present disclosure. Specifically, FIG. 11 illustrates the operation of an example process 1100. In some embodiments, the process 1100 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 1100 is executed by one or more specially configured computing devices, such as the fault support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the fault support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in the fault support apparatus 200, for example, in the memory 204 and / or another component shown and / or described herein, and / or otherwise accessible to the fault support apparatus 200, to perform the operations as described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatus, systems, devices, etc. to perform one or more of the operations as shown and described. For purposes of simplicity of explanation, the process 1100 is described as being performed by and from the perspective of the fault support apparatus 200.

[0165] Process 1100 begins at operation 1102. In some embodiments, process 1100 begins after one or more operations shown and / or described with respect to any of the other processes described herein. For example, in some embodiments as described, process 1100 begins after execution of operation 910. In this regard, some or all of process 1100 may replace or complement one or more blocks shown and / or described with respect to any of the other processes described herein. Upon completion of process 1100, the flow of operations may end. Additionally or alternatively, as shown, upon completion of process 1100, the flow may return to one or more operations of another process. It should be understood that in some embodiments, process 1100 embodies a sub-process of one or more other processes, such as process 900.

[0166] The defect support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for receiving updated defect text description data at operation 1102. In some embodiments, the updated defect text description data is received in response to a user input updating the defect text description data. The updated defect text description data may indicate and / or otherwise include additional data associated with the operation of one or more network-connected devices, the operation of the communication network, and / or the defect to be resolved. In some embodiments, the updated defect text description data may include previously submitted and / or received defect text description data in addition to new additional defect text description data.

[0167] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for applying the device activity data and the updated fault text description data to the operational support processing data model in operation 1104. The device activity data and / or the updated fault text description data are applied to select an updated predicted operational support data object from the operational support management repository. In this regard, the updated predicted operational support data object may embody a different operational support data object that is scored higher by the operational support processing data model based at least in part on the updated fault text description data. For example, the updated fault text description data may provide more detailed data associated with a fault affecting the requesting client device, the associated network connected device, and / or the communication network. Thus, the operational support processing data model may utilize such additional details to better identify a particular fault classification identifier for a fault affecting the requesting client device, the associated network connected device, and / or the communication network.

[0168] In some embodiments, the device activity data and the updated fault text description data may be applied to the operational support process data model in real time upon receiving the updated fault text description data. For example, each time updated fault text description data is received, the fault support apparatus 200 may reapply the device activity data and at least the updated fault text description data to the operational support process data model in real time. In this regard, the fault support apparatus 200 advantageously selects in real time a predicted operational support data object that is determined to be most likely to address one or more indicated faults, since additional context can be derived from the received updated data.

[0169] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for outputting an updated predicted operational support data object to a requesting client device in real time at operation 1106. The updated predicted operational support data object may be output to the requesting client device in the manner described herein with respect to operation 910. In this regard, a support user interface may be rendered that advantageously includes interface elements for accessing and / or otherwise representing the updated predicted operational support data object. Such updated rendering ensures that the support user interface continues to include at least such interface elements for accessing the most recently selected operational support data object as most likely to assist in resolving one or more faults. The updated predicted operational support data object may be output by itself and / or together with one or more previously selected predicted operational support data objects. Additionally or alternatively, in some embodiments, the updated predicted operational support data object may be rendered within the support user interface to replace a representation associated with a previously selected predicted operational support data object or to be rendered along with one or more previously selected operational support data objects. In this regard, the support user interface advantageously enables a user to access any of the predicted operational support data objects that the user prefers or determines are most likely to assist in resolving one or more faults.

[0170] FIG. 12 illustrates a flow chart showing an example operation of an example process for applying support search data according to at least some example embodiments of the present disclosure. Specifically, FIG. 12 illustrates the operation of an example process 1200. In some embodiments, the process 1200 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 1200 is executed by one or more specially configured computing devices, such as the defect support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the defect support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in the defect support apparatus 200, for example, in the memory 204 and / or another component shown and / or described herein, and / or otherwise accessible to the defect support apparatus 200, to perform the operations as described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatus, systems, devices, etc. to perform one or more of the operations as shown and described. For purposes of ease of explanation, the process 1200 is described as being performed by and from the perspective of the fault support apparatus 200.

[0171] Process 1200 begins at operation 1202. In some embodiments, process 1200 begins after one or more operations shown and / or described with respect to any of the other processes described herein. For example, in some embodiments as described, process 1200 begins after execution of operation 906. In this regard, some or all of process 1200 may replace or complement one or more blocks shown and / or described with respect to any of the other processes described herein. Upon completion of process 1200, the flow of operations may end. Additionally or alternatively, as shown, upon completion of process 1200, the flow may return to one or more operations of another process. For example, as shown, the flow may return to operation 908 upon completion of process 1200. It should be understood that in some embodiments, process 1200 embodies a sub-process of one or more other processes, such as process 900.

[0172] The defect support device 200 includes means, such as the support providing circuit 210, the communication circuit 208, the input / output circuit 206, the processor 202, etc., or a combination thereof, for receiving support search data associated with a defect support session at operation 1202. The support search data may embody defect text description data entered (e.g., by a user or automatically in response to a data-driven process) via a requesting client device indicating a particular defect to be resolved and / or otherwise associated with this particular defect. In some embodiments, receiving the support search data by the defect support device 200 indicates a request to initiate a defect support session, for example, associated with resolving the particular defect indicated in the support search data. For example, the support search data may include text data representing "I can't connect my printer," which may be processed to indicate a problem with connecting a particular network-connected device (e.g., a printer) to a home network.

[0173] The defect support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for applying the support search data to the operational support process data model to select predicted operational support data objects in operation 1204. In this regard, the defect support apparatus 200 may apply the support search data to the operational support process data model as defect text description data and / or other support activity data in the manner described with respect to operation 908.

[0174] FIG. 13 illustrates a flow chart showing an example operation of an example process for training an operational support processing data model according to at least some example embodiments of the present disclosure. Specifically, FIG. 13 illustrates the operation of an example process 1300. In some embodiments, the process 1300 is embodied by computer program code stored in a non-transitory computer-readable storage medium of a computer program product configured to execute to perform the process as shown and described. Alternatively or additionally, in some embodiments, the process 1300 is executed by one or more specially configured computing devices, such as the fault support apparatus 200 alone or in communication with one or more other components, devices, systems, etc. In this regard, in some such embodiments, the fault support apparatus 200 is specially configured by computer-coded instructions (e.g., computer program instructions) stored in the fault support apparatus 200, for example, in the memory 204 and / or another component shown and / or described herein, and / or otherwise accessible to the fault support apparatus 200, to perform the operations as described. In some embodiments, the fault support apparatus 200 communicates with one or more external apparatus, systems, devices, etc. to perform one or more of the operations as shown and described. For purposes of simplicity of explanation, the process 1300 is described as being performed by and from the perspective of the fault support apparatus 200.

[0175] Process 1300 begins at operation 1302. In some embodiments, process 1300 begins after one or more operations shown and / or described with respect to any of the other processes described herein. In this regard, some or all of process 1300 may replace or complement one or more blocks shown and / or described with respect to any of the other processes described herein. Upon completion of process 1300, the flow of operations may end. Additionally or alternatively, as shown, upon completion of process 1300, the flow may return to one or more operations of another process. For example, as shown, the flow may return to operation 902 upon completion of process 1300. It should be understood that in some embodiments, process 1300 embodies a sub-process of one or more other processes, such as process 900.

[0176] The defect support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for identifying the operational support data object set at operation 1302. In some embodiments, the defect support apparatus 200 identifies the operational support data object set from an operational support management repository storing such operational support data objects. To identify the operational support data object set, the defect support apparatus 200 may query the operational support management repository for all stored operational support data objects and / or a portion of the operational support data objects. In some embodiments, the defect support apparatus 200 maintains and / or otherwise controls the operational support management repository. In other embodiments, the operational support management repository is maintained by a separate and / or associated system, and the defect support apparatus 200 identifies the operational support data object set by accessing the operational support management repository.

[0177] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for identifying training device activity data at operation 1304. In some embodiments, the fault support apparatus 200 identifies the training device activity data from a device activity data repository that includes historical device activity data associated with any number of network-connected devices, user profiles, communication networks, etc. The device activity data repository may be maintained by the fault support apparatus 200 and / or one or more associated systems. For example, in some embodiments, the fault support apparatus 200 stores in the device activity data repository device activity data received and / or otherwise detected over time for any of a number of network-connected devices, communication networks, etc. Alternatively or additionally, in some embodiments, a separate data system associated with the fault support apparatus 200 maintains the device activity data repository, for example, by receiving, requesting, and / or otherwise detecting device activity data associated with one or more network-connected devices, communication networks, etc.

[0178] In some embodiments, the training device activity data includes an association between one or more portions of the historical device activity data and a fault classification identifier with which such portions are associated. In this regard, such association may be embodied by a manually entered and / or automatically determined label linked to an associated portion of the device activity data that indicates a fault classification identifier with which the portion of the device activity data is associated.

[0179] The fault support apparatus 200 includes means, such as the support providing circuitry 210, the communication circuitry 208, the input / output circuitry 206, the processor 202, etc., or a combination thereof, for training an operations support processing data model for selecting an operations support data object from the set of operations support data objects based at least in part on the training device activity data, at operation 1306. In some embodiments, the operations support processing data model is trained to select operations support data objects associated with fault classification identifiers determined as most likely to represent faults affecting a network connected device, a communications network, etc., represented in the device activity data and / or associated with the device activity data. In some embodiments, the operations support processing data model is trained based on additional training data, such as training support activity data, training fault text description data, etc. In this regard, In some embodiments, the operations support process data model may be trained to identify probable fault classification identifier sets based at least on the training device activity data set. For example, the operations support process data model may process the training device activity data to configure hyperparameters and / or other configurable settings of the operations support process data model based on trends, patterns, and / or values ​​represented in the training data, alone and / or in conjunction with one or more other portions of the training data, such as the training fault text description data and / or other training support activity data. The operations support process data model may be trained to score various fault classification identifiers and select predicted operations support data objects associated with the highest scoring fault classification identifiers and / or associated with scoring fault classification identifiers above a certain score threshold.

[0180] Alternatively or additionally, in some embodiments, the operational support process data model may be trained to score various operational support data objects associated with a particular fault classification identifier. In this regard, the score generated for each operational support data object may represent a confidence level of the system that the operational support data object would assist in resolving the fault represented by the particular fault classification identifier. The operational support process data model may be trained to score each operational support data object associated with a particular fault classification identifier and select the highest scoring operational support data object for output as the predicted operational support data object. Alternatively or additionally, in some embodiments, the operational support process data model is trained to score each operational support data object associated with a particular fault classification identifier and select all operational support data objects that meet a particular score threshold as the predicted operational support data object.

[0181] In some embodiments, the operations support process data model may additionally or alternatively associate each possible fault classification identifier of the set of possible fault classification identifiers with at least a portion of the set of operations support data objects. For example, the operations support process data model may process each operations support data object of the set of operations support data objects to identify possible fault classification identifiers associated with the operations support data object (e.g., possible fault classification identifiers that represent faults that the operations support data object may assist in resolving).

[0182] conclusion Although an exemplary processing system has been described above, implementations of the subject matter and functional operations described herein may be implemented in other types of digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed herein and their structural equivalents, or in combinations of one or more of these.

[0183] Embodiments of the subject matter and operations described herein may be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed herein and their structural equivalents, or a combination of one or more of them. Embodiments of the subject matter described herein may be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a computer storage medium for execution by or to control the operation of an information / data processing apparatus. Alternatively, or in addition, the program instructions may be encoded in an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information / data for transmission to a suitable receiver apparatus for execution by the information / data processing apparatus. The computer storage medium may be, or may be included in, a computer readable storage device, a computer readable storage substrate, a random or serial access memory array or device, or a combination of one or more of them. Furthermore, the computer storage medium is not a propagating signal, but the computer storage medium may be a source or destination of computer program instructions encoded in an artificially generated propagated signal. A computer storage medium may also be, or be contained in, one or more separate physical components or media (eg, multiple CDs, disks, or other storage devices).

[0184] The operations described herein may be implemented as operations performed by an information / data processing apparatus on information / data stored in one or more computer-readable storage devices or received from other sources.

[0185] The term "data processing apparatus" encompasses any kind of apparatus, device, and machine for processing data, including, by way of example, a programmable processor, a computer, a system on a chip, or a plurality or combination of the foregoing. The apparatus may include special purpose logic circuitry, such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC). In addition to hardware, the apparatus may also include code that creates an execution environment for the computer program in question, such as code that constructs a processor firmware, a protocol stack, a repository management system, an operating system, a cross-platform runtime environment, a virtual machine, or one or more combinations thereof. The apparatus and execution environment may implement a variety of different computing model infrastructures, such as web services, distributed computing, and grid computing infrastructures.

[0186] A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted, declarative or procedural, and can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or information / data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in several coordinated files (e.g., a file that stores one or more modules, subprograms, or portions of code). A computer program can be deployed to be executed on one computer, or on several computers that are located at one site or distributed across several sites and interconnected by a communication network.

[0187] The processes and logic flows described herein may be executed by one or more programmable processors executing one or more computer programs to perform actions by operating on input information / data and generating output. Processors suitable for executing computer programs include, by way of example, both general-purpose and special-purpose microprocessors, and one or more processors of any type of digital computer. Generally, a processor receives instructions and information / data from a read-only memory or a random access memory, or both. The essential elements of a computer are a processor for performing actions according to the instructions, and one or more memory devices for storing instructions and data. Generally, a computer also includes one or more mass storage devices, such as magnetic disks, magneto-optical disks, or optical disks, for storing data, or is operatively coupled to receive information / data from them, or to transfer information / data to them, or both. However, a computer need not have such devices. Suitable devices for storing computer program instructions and information / data include all forms of non-volatile memory, media, and memory devices, including, by way of example, semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices, magnetic disks, e.g., internal hard disks or removable disks, magneto-optical disks, e.g., CD-ROM and DVD-ROM disks. The processor and memory may be supplemented by, or incorporated in, special purpose logic circuitry.

[0188] To provide for user interaction, embodiments of the subject matter described herein may be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information / data to the user, and a pointing device, e.g., a mouse or trackball, by which the user can provide input to the computer. Other types of devices may also be used to provide for user interaction, e.g., feedback provided to the user may be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback, and input from the user may be received in any form, including acoustic, speech, or tactile input. Additionally, the computer may interact with the user by sending and receiving documents to and from a device used by the user, e.g., by sending a web page to a web browser on the user's client device in response to a request received from the web browser.

[0189] An embodiment of the subject matter described herein may be implemented in a computing system that includes a back-end component, e.g., as an information / data server, or includes a middleware component, e.g., an application server, or includes a front-end component, e.g., a client computer having a graphical user interface or web browser through which a user may interact with an implementation of the subject matter described herein, or includes any combination of one or more such back-ends, middleware, or fronts. The components of the system may be interconnected by any form or medium of digital information / data communication, e.g., a communications network. Examples of communications networks include local area networks ("LANs") and wide area networks ("WANs"), networks-to-networks (e.g., the Internet), and peer-to-peer networks (e.g., ad-hoc peer-to-peer networks).

[0190] A computing system may include clients and servers. Clients and servers are generally remote from each other and typically interact through a communications network. The relationship of clients and servers arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In some embodiments, a server transmits information / data (e.g., HTML pages) to a client device (e.g., for the purpose of displaying the information / data to a user interacting with the client device and receiving user input). Information / data generated at the client device (e.g., results of user interaction) may be received from the client device at the server.

[0191] Although the present specification contains many specific implementation details, these should not be construed as limiting the scope of any disclosure or what may be claimed, but as describing features specific to certain embodiments of a particular disclosure. Certain features described in the present specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Furthermore, even if features are described above as acting in a particular combination and initially claimed as such, one or more features from the claimed combination may in some cases be carved out of the combination, and the claimed combination may be subject to subcombinations or variations of the subcombination.

[0192] Similarly, although operations are depicted in the figures in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown, or in the sequential order, or that all of the illustrated operations be performed, to achieve desirable results. In certain situations, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the program components and systems described may generally be integrated together in a single software product or packaged into multiple software products.

[0193] Thus, certain embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In certain implementations, multitasking and parallel processing may be advantageous.

[0194] Non-limiting exemplary embodiments of the present disclosure Having described various aspects of the present invention, it will be understood that various embodiments are described herein. The subject matter described in the specification includes, but is not limited to, the following specific embodiments. These embodiments are merely examples and should not be construed as limiting the scope of the disclosure. It will be understood that the embodiments in some aspects can be freely combined. In other aspects of the disclosure, each embodiment is independent of the other embodiments described.

[0195] Embodiment 1. A computer-implemented method comprising: initiating an issue support session associated with a requesting client device; Correlating the device activity data and the defect text description data to the defect support session; applying, in real time, the device activity data and the fault text description data to an operations support process data model to select predicted operations support data objects from the systems operations support management repository, the operations support process data model being trained based on training device activity data and fault history data from the systems operations support management repository; and outputting, in real time, the predicted operational support data objects to a requesting client device.

[0196]

[0021] Embodiment 2: The method further includes receiving, via a requesting client device, a user input requesting initiation of a problem support session; 2. The computer-implemented method of embodiment 1, wherein the predicted operational support data object is output in response to receiving user input requesting initiation of a problem support session.

[0197]

[0023] Embodiment 3: Receiving user input involving an operational support data object through a requesting client device; 3. The computer-implemented method of embodiment 1 or 2, further comprising: terminating the initiation of the problem support session in response to receiving user input involving the operational support data object.

[0198] Embodiment 4: A computer-implemented method described in any one of embodiments 1 to 3, further comprising terminating a process for establishing a connection between the requesting client device and the technician device in response to receiving user input involving an operational support data object.

[0199] Embodiment 5: Receiving updated fault text description data in response to a user input updating the fault text description data; Upon receiving the fault text description data, automatically applying the device activity data and the updated fault text description data to an operations support processing data model in real time to select updated predicted operations support data objects from the system operations support management repository; 5. The computer-implemented method of any one of embodiments 1 to 4, further comprising: outputting the updated predicted operational support data object to the requesting client device.

[0200]

[0021] Embodiment 6: The method further includes receiving support search data associated with the defect support session; A computer-implemented method according to any one of embodiments 1 to 5, wherein the support search data is further applied to an operational support process data model to select predicted operational support data objects.

[0201]

[0023] Embodiment 7: Outputting the predicted operational support data object to a requesting client device in real time, A computer-implemented method as described in any one of embodiments 1 to 6, comprising causing a requesting client device to render a support user interface including a first sub-interface associated with a main support transmission process and a second sub-interface including predicted operational support data objects.

[0202] Embodiment 8: Identifying an operational support data object set; Identifying training device activity data; The operational support processing data model, identifying a set of probable fault classification identifiers based at least on the training device activity data; and The computer-implemented method of any one of embodiments 1 to 7, further comprising: training each potential fault classification identifier of the set of potential fault classification identifiers to be associated with at least a portion of the set of operational support data objects.

[0203] Embodiment 9: A computer-implemented method as described in any one of embodiments 1 to 8, wherein the dynamic home communication network includes a plurality of network-connected devices associated with a plurality of network-connected device types, and the operational support processing data model selects predicted operational support data objects based at least in part on the plurality of network-connected device types.

[0204] Embodiment 10: A computer-implemented method described in any one of embodiments 1 to 9, wherein the device activity data indicates a plurality of faults represented by a plurality of fault classification identifiers, and the predicted operational support data object is associated with a first fault classification identifier representing a first fault among the plurality of faults that contributes to each other fault among the plurality of faults.

[0205]

[0023] Embodiment 11: Identifying a user profile associated with a requesting client device; The computer-implemented method of any one of embodiments 1 to 10, further comprising: determining, based at least in part on the user profile, that the device activity data includes at least device identification data for one or more network-connected devices associated with the dynamic home communication network.

[0206]

[0023] Embodiment 12: Initiating a problem support session associated with a requesting client device includes: A computer-implemented method as described in any one of embodiments 1 to 11, comprising initiating a process for establishing a connection between a requesting client device and a technician device associated with a technical personnel, wherein a predicted operational support data object is output before establishing the connection.

[0207] Embodiment 13: A computer-implemented method according to any combination of embodiments 1 to 12. Embodiment 14: An apparatus comprising at least one processor and at least one non-transitory memory having computer program code stored therein, the computer program code, when executed on the at least one processor, causing the apparatus to perform any one of the computer-implemented methods of embodiments 1 to 13.

[0208] Embodiment 15: A computer program product comprising at least one non-transitory computer-readable storage medium having computer program code stored thereon, the computer program code configuring the computer program product, when executed on at least one processor, to perform any one of the computer-implemented methods of embodiments 1 to 13.

Claims

1. 1. An apparatus for selecting predicted operational support data objects from an operational support management repository using device activity data from a dynamic home communications network, the apparatus comprising: at least one processor; and at least one memory having stored thereon computer-coded instructions, the computer-coded instructions, when executed by the at least one processor, causing the apparatus to: initiating an issue support session associated with a requesting client device; correlating device activity data and problem text description data to the problem support session; applying, in real time, the device activity data and the fault text description data to an operations support process data model to select, from the operations support management repository, the predicted operations support data object, the operations support process data model having been trained based on training device activity data and fault history data from the operations support management repository; outputting the predicted operational support data objects to the requesting client device in real time.

2. The apparatus further comprises: receiving, via the requesting client device, a user input requesting initiation of the problem support session; The apparatus of claim 1 , wherein the predicted operational support data object is output in response to receiving the user input requesting initiation of the fault support session.

3. The apparatus further comprises: receiving user input via the requesting client device involving an operational support data object; The apparatus of claim 1 , further comprising: terminating the initiation of the fault support session in response to receiving the user input involving the operational support data object.

4. The apparatus further comprises: receiving updated fault text description data in response to user input updating the fault text description data; upon receiving the fault textual description data, automatically applying the device activity data and the updated fault textual description data to the operations support process data model in real time to select updated predicted operations support data objects from the operations support management repository; 2. The apparatus of claim 1, further comprising: outputting the updated forecasted operational support data object to the requesting client device.

5. The apparatus, further configured to receive support search data associated with the defect support session; The apparatus of claim 1 , wherein the support search data is further applied to the operational support process data model to select the predicted operational support data objects.

6. to output the predicted operational support data objects to the requesting client device in real time, the apparatus comprising: The apparatus of claim 1 , configured to cause, to the requesting client device, rendering of a support user interface including a first sub-interface associated with a main support transmission process and a second sub-interface including the predicted operational support data object.

7. The apparatus further comprises: Identifying a set of operational support data objects; identifying said training device activity data; The operational support process data model, identifying a set of probable fault classification identifiers based at least on the training device activity data; and 2. The apparatus of claim 1, further comprising: training each potential fault classification identifier of the set of potential fault classification identifiers for association with at least a portion of the set of operational support data objects.

8. 2. The apparatus of claim 1, wherein the dynamic home communications network includes a plurality of network-connected devices associated with a plurality of network-connected device types, and the operational support process data model selects the predicted operational support data object based at least in part on the plurality of network-connected device types.

9. 2. The apparatus of claim 1, wherein the device activity data indicates a plurality of faults represented by a plurality of fault classification identifiers, and the predicted operational support data object is associated with a first fault classification identifier representing a first fault of the plurality of faults that contributes to each other fault of the plurality of faults.

10. The apparatus further comprises: identifying a user profile associated with the requesting client device; 2. The apparatus of claim 1, further comprising: determining, based at least in part on the user profile, that the device activity data includes at least device identification data for one or more network-connected devices associated with the dynamic home communications network.

11. to initiate the problem support session associated with the requesting client device, 2. The apparatus of claim 1, further comprising: initiating a process for establishing a connection between the requesting client device and a technician device associated with a technician, the predicted operational support data object being output prior to establishing the connection.

12. The apparatus further comprises:

12. The apparatus of claim 11, further comprising: terminating the process for establishing the connection between the requesting client device and the technician device in response to receiving user input involving an operational support data object.

13. 1. A computer-implemented method for selecting predicted operational support data objects from an operational support management repository using device activity data from a dynamic home communications network, the computer-implemented method comprising: initiating an issue support session associated with a requesting client device; correlating device activity data and problem text description data to the problem support session; applying, in real time, the device activity data and the fault text description data to an operations support process data model to select, from the operations support management repository, the predicted operations support data object, the operations support process data model having been trained based on training device activity data and fault history data from the operations support management repository; and outputting the predicted operational support data objects to the requesting client device in real time.

14. outputting the predicted operational support data objects to the requesting client device in real time; 14. The computer-implemented method of claim 13, further comprising causing, to the requesting client device, rendering of a support user interface including a first sub-interface associated with a main support transmission process and a second sub-interface including the predicted operational support data object.

15. The computer-implemented method further comprises: Identifying a set of operational support data objects; identifying said training device activity data; The operational support process data model, identifying a set of probable fault classification identifiers based at least on the training device activity data; and 14. The computer-implemented method of claim 13, further comprising: training each potential fault classification identifier of the set of potential fault classification identifiers for association with at least a portion of the set of operational support data objects.

16. 14. The computer-implemented method of claim 13, wherein the device activity data indicates a plurality of faults represented by a plurality of fault classification identifiers, and the predicted operational support data object is associated with a first fault classification identifier representing a first fault of the plurality of faults that contributes to each other fault of the plurality of faults.

17. initiating the problem support session associated with the requesting client device; 14. The computer-implemented method of claim 13, further comprising initiating a process for establishing a connection between the requesting client device and a technician device associated with a technician, wherein the predicted operational support data object is output prior to establishing the connection.

18. The computer-implemented method further comprises:

20. The computer-implemented method of claim 17, further comprising terminating the process for establishing the connection between the requesting client device and the technician device in response to receiving the user input involving an operational support data object.

19. 1. A computer program product for selecting predicted operational support data objects from an operational support management repository using device activity data from a dynamic home communications network, the computer program product comprising at least one non-transitory computer readable storage medium having computer program code stored thereon, the computer program code, when executed on at least one processor, causing the computer program product to: initiating an issue support session associated with a requesting client device; correlating device activity data and problem text description data to the problem support session; applying, in real time, the device activity data and the fault text description data to an operations support process data model to select, from the operations support management repository, the predicted operations support data object, the operations support process data model having been trained based on training device activity data and fault history data from the operations support management repository; and outputting the predicted operational support data objects to the requesting client device in real time.

20. initiating the problem support session associated with the requesting client device; and initiating a process for establishing a connection between the requesting client device and a technician device associated with a technician, the predicted operational support data object being output prior to establishing the connection, the computer program product comprising:

20. The computer program product of claim 19, further configured to terminate the process for establishing the connection between the requesting client device and the technician device in response to receiving user input involving an operational support data object.

Images