Operation assisting method and system, electronic equipment, storage medium and program product

Abstract

The invention discloses an operation assisting method and system, electronic equipment, a storage medium and a program product. The operation assisting method applied to a server side comprises the steps that operation intention information provided by a user side is acquired; the operation intention information is used for representing an operation intention of the user on the target digital product; according to the operation intention information, using a preset model to generate auxiliary execution information of the operation process; the operation process is used for realizing operation intention; the preset model is obtained by training an artificial intelligence model by using the operation knowledge information; the operation knowledge information is used for describing an operation process of each operation which can be executed on the target digital product; and sending auxiliary execution information of the operation process to the user side. According to the method and the device, customized technical support can be provided for the user, the intervention of manual technical support is reduced, and the cost of technical support is reduced. And moreover, the use threshold of the user for using the digital product is reduced, and the use efficiency of the user is improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, specifically to an operation assistance method, system, electronic device, storage medium, and program product. Background Technology

[0002] When users use certain functions of digital products such as software, website pages, cloud services, or cloud products, some functions are complex to use or the user is unfamiliar with the operation. Users need to spend a lot of time looking at the function descriptions or related technical documents. If the user's problem cannot be solved, the user needs to seek manual technical support from the digital product provider, which is very costly. Summary of the Invention

[0003] The purpose of this application is to address the shortcomings of the prior art by providing an operation assistance method, system, electronic device, storage medium, and program product, thereby at least solving the deficiencies of the prior art. This purpose is achieved through the following technical solutions.

[0004] The first aspect of this application proposes an operation assistance method, which is applied to a server and includes:

[0005] Obtain operation intent information provided by the user terminal; the operation intent information is used to represent the user's operation intent on the target digital product;

[0006] Based on the operation intent information, auxiliary execution information for the operation process is generated using a preset model; the operation process is used to realize the operation intent; the preset model is obtained by training an artificial intelligence model using operation knowledge information; the operation knowledge information is used to describe the operation process of each operation that can be performed on the target digital product;

[0007] Send auxiliary execution information of the operation process to the user terminal.

[0008] A second aspect of this application proposes an operation assistance method, which is applied to a user terminal and includes:

[0009] Send the user's operation intent information to the server; the operation intent information is used to represent the user's operation intent on the target digital product;

[0010] The system receives auxiliary execution information of the operation process returned by the server; the operation process is used to realize the operation intention; the auxiliary execution information of the operation process is generated by the server using a preset model based on the operation intention information; the preset model is obtained by training an artificial intelligence model using operation knowledge information; the operation knowledge information is used to describe the operation process of each operation that can be performed on the target digital product.

[0011] Based on the auxiliary execution information of the operation process, perform auxiliary operations for the operation process.

[0012] A third aspect of this application proposes an operation assistance system, the system comprising a cloud product console and a cloud server, the cloud product console being used to provide an interface for managing cloud products;

[0013] The cloud product console is used to obtain user's operation intent information for the cloud product through the interface, and send the operation intent information to the cloud server. The operation intent information is used to represent the user's operation intent for the cloud product.

[0014] The cloud server is used to generate auxiliary execution information of the operation process using a preset model based on the operation intent information, and send the auxiliary execution information of the operation process to the cloud product console; the preset model is obtained by training an artificial intelligence model using operation knowledge information; the operation knowledge information is used to describe the operation process of each operation that can be performed on the cloud product;

[0015] The cloud product console is used to receive auxiliary execution information for the operation process and to perform auxiliary operations for the operation process based on the auxiliary execution information.

[0016] The fourth aspect of this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the method as described in the first or second aspect above.

[0017] The fifth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the method as described in the first or second aspect above.

[0018] The sixth aspect of this application provides a computer program product comprising a computer program that is executed by a processor to perform the method as described in the first or second aspect above.

[0019] Based on the method described in the first or second aspect above, this application has at least the following beneficial effects or advantages:

[0020] The client obtains the user's operation intent information and sends it to the server. Based on the operation intent information, the server uses a preset model to generate auxiliary execution information for the operation process and returns this information to the client. The client can use this auxiliary execution information to assist the user in executing the operation process to achieve the user's operation intent. The preset model used by the server is obtained by training an artificial intelligence model based on operation knowledge information. The operation knowledge information used for training describes the operation process of each operation that can be performed on the target digital product. Therefore, the preset model can learn the operation process of each operation, thereby generating auxiliary execution information that matches the user's operation intent based on understanding the user's operation intent. This embodiment of the application can provide customized technical support to users based on their individual operation intent, reducing the need for manual technical support and lowering the cost of technical support. Furthermore, by assisting users in executing the operation process with auxiliary execution information to achieve their operation intent, it not only lowers the barrier to entry for users of digital products but also improves user efficiency and enhances the user experience.

[0021] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application, it can be implemented according to the contents of the specification. In order to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0022] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0023] Figure 1 This is a flowchart illustrating an operation assistance method provided according to some embodiments of the related art;

[0024] Figure 2 This is a schematic diagram of the structure of an operation assistance system provided according to some embodiments of this application;

[0025] Figure 3 This is a schematic diagram of the structure of an operation assistance system according to some embodiments of this application;

[0026] Figure 4 This is a flowchart illustrating an operation assistance method applied to a server according to some embodiments of this application;

[0027] Figure 5 This is a schematic diagram of a user interface for an operation assistance method provided according to some embodiments of this application;

[0028] Figure 6This is a flowchart illustrating an operation assistance method applied to a user terminal according to some embodiments of this application;

[0029] Figure 7 This is a schematic diagram of a user interface for an operation assistance method provided according to some embodiments of this application;

[0030] Figure 8 This is a flowchart illustrating an operation assistance method provided according to some embodiments of this application;

[0031] Figure 9 This is a schematic diagram of the structure of an operation assistance device applied to a server according to some embodiments of this application;

[0032] Figure 10 This is a schematic diagram of the structure of an operation assistance device applied to a user terminal according to some embodiments of this application;

[0033] Figure 11 This is a schematic diagram of the hardware structure of an electronic device according to some embodiments of this application. Detailed Implementation

[0034] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0035] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0036] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0037] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0038] Digital products have high barriers to entry, cumbersome operation processes, low user efficiency, and high technical support costs. Take cloud services or products as an example: with the continuous development of cloud computing technology, more and more enterprises are adopting cloud products and services for data processing and storage. Cloud services and products typically have complex functions and are updated very rapidly. The cloud product console, as a web interface provided to users for managing and configuring cloud products and services, often has a complex interface and cumbersome operation processes. In this situation, users need to spend time reading product documentation and practicing to understand and master the functions of the cloud product console, especially those deep functions that are not easily discovered. These deep functions are difficult for users to find directly in the product interface, or require users to perform multiple steps to access them, making it difficult for novice users to find the function entry points and use them effectively. These deeper functionalities often offer more customization options and advanced control capabilities. For example, they can customize dashboards according to individual user needs, display key performance indicators or data views of different cloud products, help users analyze and predict the cost of using cloud services for cost control, and allow technically skilled users to integrate cloud products into other systems or applications through APIs (Application Programming Interfaces).

[0039] A related technology provides an implementation method to help users master the functions of the cloud product console. For example... Figure 1As shown, the process includes the following steps: Step 101, the user opens the cloud product console interface and enters the cloud product console. Step 102, if the user has operational problems or questions about product functions, proceed to Step 103 to view the product documentation. Alternatively, after Step 101, the user can directly proceed to Step 103 to view the product documentation provided by the cloud product console to learn how to operate the cloud product. The product documentation may include detailed information about the cloud product, specifically including information on the configuration and operations that the user can perform on the cloud product, so that the user can learn how to operate the cloud product. After viewing the product documentation, proceed to Step 104, where the user can determine if the problem can be resolved. If so, proceed to Step 105, where the user performs configuration and management operations on the cloud product. Otherwise, if the user does not find a solution after viewing the product documentation, or does not understand the instructions in the product documentation, they can proceed to Step 106 to submit a customer service ticket to consult technical support personnel, and then proceed to Step 107, where technical support personnel will answer the user's questions.

[0040] Related technologies also provide several implementation methods to help users operate digital products such as cloud products. For example, one cloud computing platform service provides cloud resource modeling and provisioning services, which can help users automate the creation and management of various cloud resources through coding. However, when using this service, users need to write templates, which can be JSON (JavaScript Object Notation) or YAML (YAML is not Markup Language) text files, to describe the required resources and their associated attributes. Therefore, users need to have certain technical knowledge and experience to accurately use this auxiliary function, which places high demands on users and has a certain technical threshold.

[0041] To address the shortcomings of the aforementioned related technologies, embodiments of this application propose an operation assistance method and an operation assistance system. The operation assistance system provided in these embodiments can be used to apply the operation assistance method provided in these embodiments. Figure 2As shown, the operation assistance system provided in this application embodiment includes a user terminal 201 and a server terminal 202. The user terminal 201 and the server terminal 202 can communicate via a network. The user terminal 201 can be a web page, web application, desktop application, mobile application, instant messaging software, cloud service, vehicle system, or any component of the above forms, etc. The user terminal 201 provides the user with an interface for performing various operations on the target digital product. The target digital product can be a cloud service, cloud product, application, virtual resource, etc. The user can perform management and configuration operations on the target digital product, such as purchasing, configuring parameters, and creating instances, through the interface provided by the user terminal 201. The server terminal 202 is connected to the user terminal 201 via a network, responsible for processing and responding to requests from the user terminal 201, performing configuration and management of the target digital product in the background based on the user's operations on the user terminal 201, and providing technical support for operation assistance to the user terminal 201.

[0042] In the operation assistance system provided in this application embodiment, server 202 is used to execute the operation assistance method provided in this application embodiment for server 202, and user terminal 201 is used to execute the operation assistance method provided in this application embodiment for user terminal 201. User terminal 201 obtains user operation intent information and sends it to server 202. Server 202 generates auxiliary execution information for the operation process using a preset model based on the operation intent information. User terminal 201 can execute auxiliary operations for the operation process through the auxiliary execution information to assist the user in executing the operation process and realizing the user's operation intent. The preset model used by server 202 is obtained by training an artificial intelligence model based on operation knowledge information. The operation knowledge information used for training describes the operation process of each operation that can be performed on the target digital product. Therefore, the preset model can learn the operation process of each operation, thereby generating auxiliary execution information for the operation process that conforms to the user's operation intent based on understanding the user's operation intent. This application embodiment can provide customized technical support to users according to their individual operation intent, reducing the intervention of manual technical support and lowering the cost of technical support. Furthermore, by assisting users in executing operations through information, the user's operational intentions are achieved. This not only lowers the barrier to entry for users of digital products but also improves user efficiency and enhances the user experience.

[0043] In one application scenario, the target digital product is a cloud service or cloud product. Correspondingly, the user terminal in the operation assistance system is the cloud product console, and the server terminal in the operation assistance system is the cloud server. The cloud product console provides the interface for managing cloud products and interacts directly with the user. The cloud server is used to provide data to the cloud product console and process requests from the cloud product console.

[0044] like Figure 3 As shown, the operation assistance system in the above application scenario includes a cloud product console 301 and a cloud server 302 that communicate via a network. In some embodiments, the cloud product console 301 interacts with the user through a web browser, and the user can access the web interface for managing cloud products through a browser.

[0045] Users can input their operational intent information through the interface provided by the cloud product console 301, using input methods such as keyboard, mouse, and voice. This operational intent information represents the user's intention to operate the cloud product. The cloud product console 301 then sends the acquired operational intent information to the cloud server 302.

[0046] After receiving the operation intent information, the cloud server 302 can generate auxiliary execution information for the operation process using a preset model based on the operation intent information. This auxiliary execution information assists the user in executing the operation process to achieve the operation intent. The auxiliary execution may take multiple forms. Based on whether it includes automatically executing at least some of the operation steps in the operation process, the auxiliary methods can be divided into two categories. Both categories of auxiliary methods can include auxiliary methods that guide the user in executing the operation process. Specifically, the guiding auxiliary methods can include various forms, including but not limited to: text, voice, images, animation, and interface visual elements. These forms can be used individually or in combination, and are all included in the technical solutions provided in this application embodiment. The preset model used by the cloud server 302 is obtained by pre-training an artificial intelligence model using operation knowledge information. The operation knowledge information describes the operation process of each operation that can be performed on the cloud product.

[0047] After generating auxiliary execution information for the operation process, the cloud server 302 sends the auxiliary execution information to the cloud product console 301. Upon receiving the auxiliary execution information, the cloud product console 302 can execute auxiliary operations to assist the user in performing the operation process. For example, it can assist the user in performing the operation process to achieve the user's operational intent through question and answer, video playback, interface highlighting, or automatic execution.

[0048] For any parts of the operation assistance system not described in detail in this embodiment, please refer to the relevant descriptions in the operation assistance methods provided in the embodiments of this application.

[0049] The operation assistance method provided in the embodiments of this application will be described below.

[0050] like Figure 4 As shown, an operation assistance method applicable to the server side of the above-mentioned operation assistance system is provided, including the following steps 401 to 403.

[0051] Step 401: The server obtains the operation intent information provided by the user.

[0052] Operation intent information represents a user's intended action on a target digital product. Users can perform different operations on the target digital product using their client. A user's operation intent is the goal they wish to achieve through that operation. The user inputs information representing their operation intent into the client, which then obtains this information. After obtaining the operation intent information, the client can send it to the server via communication methods such as a network, allowing the server to acquire the operation intent information provided by the client.

[0053] In some implementations, the client can directly send the user's input information as operation intent information to the server. In other implementations, the client can process the user's input information to generate operation intent information and send it to the server. For example, the user can describe the operation intent through language, such as inputting "I want to purchase a cloud product of type A with a monthly subscription in a certain city for 3 months" via voice or text. Accordingly, the operation intent information can include the user's voice or text input. Alternatively, the client can preprocess the user's input to obtain the operation intent information, such as converting voice to text or adding contextual information to the text, such as adding the following text to the user's input: "Please generate auxiliary execution information for the operation process according to the user's needs," so that the preset model understands how to respond to the user's needs.

[0054] In other implementations, users can also express their operational intent by inputting operation information. For example, the user terminal can provide the user with multiple commonly used operation intent options based on big data statistics, prompting the user to select the user's operation intent from the multiple commonly used operation intent options provided. Accordingly, the user terminal can directly send the user's selection, or send the generated information after generating operation intent information based on the user's selection.

[0055] Step 402: The server generates auxiliary execution information for the operation process using a preset model based on the operation intent information.

[0056] The pre-defined model is obtained by training an artificial intelligence model using operational knowledge information. The architecture of the artificial intelligence model can utilize machine learning models, deep learning models, natural language processing models, large-scale models, etc. Operational knowledge information includes knowledge information related to the target digital product and / or the operations that can be performed on the target digital product. Specifically, operational knowledge information can include operational procedures describing the various operations that can be performed on the target digital product. Understandably, different forms of information can be used to describe the operational procedures, such as verbal descriptions (e.g., product documents, technical documents, operation manuals, etc.), visual descriptions (e.g., screenshots of user interface operations, recorded videos of the user interface operation process), and instruction descriptions (e.g., instruction scripts for recorded operational procedures), etc.

[0057] In some embodiments, the artificial intelligence model may use the GPT (Generative Pretrained Transformer) family of models. GPT is a family of natural language processing models based on the Transformer architecture. GPT models can generate text and are suitable for language understanding and generation tasks.

[0058] Artificial intelligence models, trained using descriptive information provided in operational knowledge, can learn the relationship between operational steps and the goals / functions achievable within an operational process. After receiving input operational intent information, the pre-built model can understand the user's intended goal and, based on the knowledge learned during pre-training, generate auxiliary execution information for the operational process that aligns with the intent. This auxiliary execution information assists the user in executing the operational process, which in turn fulfills the operational intent. Optionally, the auxiliary execution information can assist the user in executing the operational process through various methods, such as question-and-answer formats, displayed guidance, or automatic execution of instructions.

[0059] In some implementations, the step of generating auxiliary execution information for the operation process using a preset model can be executed locally on the server. In other implementations, the step of generating auxiliary execution information for the operation process using a preset model can be implemented by calling remote services, such as third-party services or cloud services.

[0060] Step 403: The server sends auxiliary execution information of the operation process to the user.

[0061] After generating auxiliary execution information for the operation process using a preset model, the server sends this information to the client. Upon receiving this information, the client can perform auxiliary operations based on it, assisting the user in executing the operation process and achieving the user's intended action.

[0062] The operation assistance method provided in this application embodiment is executed by a server, which may include hardware devices, software modules, or a combination of hardware devices and software modules. Hardware devices may include servers, hardware storage media, etc., and software modules may include different forms of software modules such as applications / systems / cloud services running on the hardware devices. It should be noted that the operation assistance method and the execution subject of the operation assistance method provided in this application embodiment are only used to illustrate the application scenarios of this application embodiment, and this application embodiment does not limit them.

[0063] The operation assistance method provided in this application embodiment is executed by a server. The server, based on the operation intent information provided by the user, can use a preset model to generate auxiliary execution information for the operation process. This allows the user to execute the operation process with the assistance information returned by the server, thus realizing the user's operation intent. The preset model used by the server is obtained by training an artificial intelligence model based on operation knowledge information. The operation knowledge information used for training describes the operation process of each operation that can be performed on the target digital product. Therefore, the preset model can learn the operation process of each operation, thereby generating auxiliary execution information that matches the user's operation intent based on understanding the user's operation intent. This application embodiment can provide customized technical support to users based on their individual operation intent, reducing the need for manual technical support and lowering the cost of technical support. Furthermore, by assisting users in executing operation processes with auxiliary execution information to realize their operation intent, it not only lowers the barrier to entry for users of digital products but also improves user efficiency and enhances the user experience.

[0064] In some implementations, step 402, where the server generates auxiliary execution information for the operation process using a preset model based on the operation intent information, may include the following steps: the server obtains the auxiliary method information selected by the user from the operation intent information, and the server generates auxiliary execution information corresponding to the auxiliary method information using a preset model based on the operation intent information.

[0065] The assistance method information is used to indicate the assistance method for the operation process. In some embodiments of this application, multiple types of assistance methods are provided, such as question and answer, guidance, or automatic execution. Users can choose which assistance method to use to assist in performing the operation from the multiple types of assistance methods provided. Accordingly, the assistance method information can be generated based on the user's selection.

[0066] In some embodiments, a user interface can be provided with multiple accessibility options, allowing the user to select their desired accessibility method from among several options. An example interface diagram is shown below. Figure 5 As shown. Reference Figure 5The user interface displays a navigation bar 501 on the side for operation assistance. The navigation bar 501 includes buttons for three assistance methods: a question-and-answer button 51, a navigation button 52, and an automatic operation button 53. When a user clicks a button, they indicate that they expect the corresponding assistance method to assist them in performing the operation. After obtaining the user's selected assistance method information, the user interface can attach this information to the operation intent information and send it to the server. Optionally, in some embodiments, the operation intent information may include assistance method information and intent description information, where the intent description information describes the user's operation intent. Optionally, the user interface may also send the assistance method information and intent description information separately.

[0067] After receiving the operation intent information sent by the user, the server extracts the user-selected assistance method information from the operation intent information, and then generates assistance execution information corresponding to the assistance method information. The user can then execute the corresponding assistance operation based on the assistance execution information matching the user's selected assistance method, such as asking and answering questions, providing guidance, or automatic execution. By providing multiple assistance method information, the flexibility of assistance methods can be improved, and assistance execution information can be generated according to the user's needs and preferences, thus enhancing the user experience.

[0068] Specifically, in some embodiments, the auxiliary method information indicates that the operation process is executed by the user terminal, that is, the user terminal automatically executes the operation process on behalf of the user. The server generates auxiliary execution information for the operation process corresponding to the auxiliary method information using a preset model based on the operation intent information. Specifically, this can be achieved by generating operation instructions to implement the operation process using the preset model based on the operation intent information, and then using these operation instructions as auxiliary execution information for the operation process. The operation instructions generated by the server can be automatically executed by the user terminal, improving the efficiency of realizing the user's intent and mitigating the risk of the user potentially performing incorrect operations.

[0069] Some operational intentions may be achieved through an operation flow containing one operation step, such as clicking an icon on the interface, while other operational intentions may require an operation flow containing multiple operation steps. Accordingly, the operation instructions include sub-instructions corresponding to each operation step in the operation flow, and the sub-instructions are arranged according to the order of the operation steps in the operation flow.

[0070] In some implementations, the method provided in this application may further include the following steps: the server uses a preset model to determine whether there is a target operation step in the operation process; if there is a target operation step, a confirmation instruction is added between the sub-instruction corresponding to the target operation step and the adjacent previous sub-instruction in the operation instruction.

[0071] The target operation step is a step that requires user authorization to perform a target operation on user data. User data is data related to the user, such as privacy information like personal information or data related to user payment information. Target operations involving user data may pose certain risks to user data. Specifically, operations on user privacy data include, but are not limited to: submitting or modifying the user's address, name, mobile phone number, and other personal privacy data; operations related to user assets include, but are not limited to, submitting orders requested by the user, entering payment passwords, and deleting user data. In this technical solution, if there is a critical target operation involving user data, it must be performed only after user authorization confirmation.

[0072] The operation instructions are executed automatically. Therefore, a confirmation instruction should be added before the sub-instruction corresponding to the target operation step to prompt the user for confirmation before executing the target operation step. Executing the confirmation instruction can interrupt the operation process. The confirmation instruction needs to wait for the user's confirmation or cancellation instruction. Only with the user's confirmation can the operation process continue. If the user cancels, the target operation step will not be executed, and the operation process can be terminated directly.

[0073] By adding a confirmation instruction before the sub-instruction corresponding to the target operation step, users can be given an interactive opportunity to check whether the operation intention and operation process match, preventing erroneous operations and improving the security of user data.

[0074] In other embodiments, the auxiliary method information indicates guidance for the user to perform an operation. The specific implementation of the guidance can also be varied, utilizing different media types such as sound, sight, and touch. For example, the auxiliary method for guiding the user to perform an operation could be to play a video of the operation process in a pop-up window on the interface, or to mark component icons on the interface through interactive display methods, such as highlighting operation icons, flashing operation icons, or displaying interactive indication information such as arrows near operation icons. If the user performs the correct operation based on the guidance, interactive feedback can also be given to the user through tactile means such as vibration. This application does not specifically limit the guidance method.

[0075] The steps of the server generating auxiliary execution information for the operation process corresponding to the auxiliary method information based on the operation intent information using a preset model can be as follows: The server generates operation guidance information based on the operation intent information using a preset model. The operation guidance information is used to guide the user to execute the operation process and is used as auxiliary execution information for the operation process.

[0076] By generating operation guidance information to guide users, they can intuitively understand the operation process to achieve their intended purpose, thus learning to complete the operation independently more quickly and improving user efficiency. Using different types of multimedia guidance can enrich the interaction methods with users, making the operation guidance more flexible and engaging, and reducing the time users spend learning the operation process.

[0077] In some implementations, the assistance method information represents guiding the user through an operation process using a question-and-answer interaction. The server generates auxiliary execution information for the operation process corresponding to the assistance method information using a preset model based on the operation intent information. Specifically, this can be done by: determining the user's operation question based on the operation intent information; generating the corresponding answer text using the preset model; and using the answer text as auxiliary execution information for the operation process. The user's operation question can be input into the preset model as a question text, and the preset model will generate the answer text.

[0078] Because preset models can use artificial intelligence models, their understanding and generation of language are more accurate. In some embodiments, preset models can use the architecture of natural language processing models, such as the GPT model. Preset models obtained by training natural language processing models based on operational knowledge information can respond more accurately based on user intent.

[0079] If users lack sufficient understanding of the target digital product, inaccurate, unclear, or missing information in their input may lead to errors in the pre-defined model's understanding of their true intent. However, a question-and-answer interaction allows for more timely responses. Users can adjust their questions based on the model's feedback, thus expressing their intent more accurately and quickly. This interactive format allows for real-time dynamic interaction between the user and the model, enabling users to ask questions as needed during operation and providing more precise solutions to specific problems.

[0080] In some implementations, before the server obtains the operation intent information provided by the user in step 401, the following steps may also be performed: the server obtains the behavioral feature data provided by the user, and sends a prompt message to the user if the behavioral feature data exceeds a preset threshold.

[0081] User behavior data is determined based on user actions and represents the behavioral characteristics of the interactive operations performed by the user. For example, behavior data can be information statistically obtained from certain aspects of user actions. For instance, behavior data could be the number of times a user repeatedly performs the same action within a preset time period, or the duration of inactivity after the user's most recent action.

[0082] If behavioral data exceeds a preset threshold, it indicates that the user needs assistance with execution information to achieve their intended action. For example, the preset threshold may include a preset threshold for the number of repetitions. When the number of times the user repeats the same operation within a preset time period reaches the preset threshold for the number of repetitions, a prompt message is triggered. Alternatively, the preset threshold may include a preset threshold for the duration of pause after the last operation. Based on historical operations, if it is determined that the user has paused for more than the preset threshold for the duration of pause after entering the last operation, a prompt message is triggered.

[0083] The prompt message is used to prompt the user to input their intended action. If the user's behavioral characteristics exceed a preset threshold, it is determined that the user needs assistance. A prompt message is then sent to the user via the client, prompting them to input their intended action to provide auxiliary assistance. For example, the prompt message can be displayed as a pop-up window, or an auxiliary action component can be displayed on the client interface. This auxiliary action component can be set on various interfaces of the client, or it can be set as a floating button on the client, so that the user can see the auxiliary action component when different interfaces are displayed. Prompting the user to input their intended action can be done in a visually attention-grabbing way, such as shaking or scaling the icon, to attract the user's attention.

[0084] By monitoring user behavior data, the system can automatically prompt users to input their operational intentions when preset conditions are met. This allows the system to automatically identify when users need operational assistance, thus providing more timely technical support, making users feel personalized attention, and improving user experience.

[0085] In some implementations, before the server generates auxiliary execution information for the operation process using a preset model in step 402, the following steps may also be performed: the server obtains a training dataset, which includes at least one of multimedia information, knowledge graph information, explanatory documents, and historical operation information; and trains an artificial intelligence model using the training dataset to obtain a preset model.

[0086] Multimedia information can include records of operations performed on the user interface. It can encompass various media types, such as videos, screenshots, and command sets recording standard operating procedures for certain operations performed on the user interface. Multimedia information enables artificial intelligence models to learn the interface characteristics for performing various operations on the user interface.

[0087] Knowledge graph information is used to represent the relationships between various operations and the user interface features. Interface features are the graphical features on the interface, and each operation takes graphical elements on the interface as its operation object. Different operations have different graphical features for their operation objects. Based on the relationships between various operations and graphical features on the interface in the knowledge graph information, a pre-set model can learn the specific operation objects on the interface for different operation flows. In some implementations, a complete knowledge system can be organized based on knowledge and rules such as documents and multimedia information to construct a knowledge graph.

[0088] The documentation is used to describe the target data product and can depict various detailed information about the target digital product, including but not limited to: an introduction to the target data product, functional modules, and operating procedures. The documentation may include documentation on the target digital product itself or an operation manual introducing various operating information. The documentation can be used to train artificial intelligence models to learn the attribute information of the target digital product and / or the operating procedures for each operation.

[0089] Historical operation information includes information on the historical operations performed by different users on the target digital product. By learning users' operating habits and needs, more intelligent and personalized operation guidance can be provided. In some implementations, personal information of different users can be combined with user preferences for different user types statistically derived from historical operation information, thereby providing more likely operational intent requirements for different types of users.

[0090] like Figure 6 As shown, an operation assistance method applicable to the user terminal of the aforementioned operation assistance system is provided, including steps 601 to 603. This embodiment corresponds to the above-mentioned operation assistance method applicable to the server. For parts that are not described in sufficient detail in this embodiment, please refer to the relevant descriptions in the operation assistance method applied to the server provided in this application embodiment, which will not be repeated here.

[0091] Step 601: The user sends the user's operation intention information to the server.

[0092] User intent information is used to represent a user's intended action on a target digital product. This user intent information can be obtained from the user's client before being sent to the server.

[0093] In some embodiments, the user interface may globally display operation assistance components in a floating manner. Specifically, refer to... Figure 7The operation assistance component can be displayed via a floating icon 701. Users can click the operation assistance component icon 701 in the interface and enter the user's operation intention text in the pop-up input box. Alternatively, users can press the voice button 702 provided in the operation assistance component icon 701 to start speaking. The user terminal will then use the microphone of the device carrying the user terminal to acquire the user's voice, and then convert the speech into text to obtain the operation intention information.

[0094] Step 602: The user terminal receives auxiliary execution information of the operation process returned by the server.

[0095] The auxiliary execution information for the operation process is generated by the server using a preset model based on the operation intent information. This auxiliary execution information assists the user in executing the operation process, which is used to realize the operation intent. The preset model is obtained by training an artificial intelligence model using operation knowledge information, which includes operation processes describing the various operations that can be performed on the target digital product. Specific implementation methods for generating auxiliary execution information on the server side can be found in the operation assistance method applied to the server provided in the embodiments of this application, and will not be repeated here.

[0096] Step 603: The user terminal performs auxiliary operations for the operation process based on the auxiliary execution information of the operation process.

[0097] After receiving the auxiliary execution information of the operation process from the server, auxiliary operations can be performed based on the auxiliary execution information of the operation process to help the user execute the operation process and realize the user's operation intention.

[0098] The operation assistance method provided in this application embodiment is executed by the user terminal. After obtaining the user's operation intention information, the user terminal sends it to the server. The server can then generate auxiliary execution information for the operation process based on the operation intention information using a preset model. The user terminal can use the auxiliary execution information of the operation process fed back by the server to assist the user in executing the operation process and realize the user's operation intention. Since the preset model used by the server is obtained by training an artificial intelligence model based on operation knowledge information, and the operation knowledge information used for training describes the operation process of each operation that can be performed on the target digital product, the preset model can learn the operation process of each operation, thereby generating auxiliary execution information for the operation process that conforms to the user's operation intention based on understanding the user's operation intention. This application embodiment can provide customized technical support for users according to their individual operation intentions, reducing the intervention of human technical support and lowering the cost of technical support. Furthermore, by assisting users in executing the operation process through auxiliary execution information to realize their operation intentions, it not only lowers the threshold for users to use digital products but also improves user efficiency and enhances the user experience.

[0099] In some embodiments, before executing step 601 (user client sending user's operation intent information to server), the method may further include performing the following steps: The user client detects a trigger event of an operation assistance component in the current interface and displays multiple selection components. The user client detects the triggered selection component. The user submits intent description information, which describes the operation intent. The user client generates operation intent information based on the intent description information and the assistance method information corresponding to the triggered selection component.

[0100] In some embodiments, the operation assistance component can be globally displayed in at least part or all of the user interface for easy access by the user. Optionally, the operation assistance component can be displayed floatingly or embedded in the interface, such as as a floating icon. In other embodiments, the operation assistance component can be normally hidden and triggered by user input, for example, the user can call up the operation assistance component through certain specified key combinations.

[0101] Each selection component corresponds to different assistance mode information, which indicates how the operation process is assisted. The trigger event for the operation assistance component is determined based on the user's input. For example, an operation assistance component can be a button icon, and the user can trigger the display of multiple selection components by clicking with the mouse or inputting key combinations on the keyboard.

[0102] Multiple selection components correspond one-to-one with multiple different types of assistance methods. Once the user selects one, the triggered selection component is detected, thus determining the user's desired assistance method. The user can input intent description information through the input methods provided by the assistance components, such as text, voice, or interface operations, to describe their intention. It can be understood that the steps of the user detecting the trigger event of the assistance component in the current interface and the steps of the user receiving the submitted intent description information can be independent, and the execution order of these steps can be interchanged. After receiving the user's input intent description information and selected assistance method information, the user can generate operation intent information.

[0103] By providing a variety of different selection components through the user interface, corresponding to different assistance methods, users can choose which type of assistance to use, which increases the user's autonomy in choice and the flexibility of assistance methods, thereby improving the user experience.

[0104] In some embodiments, the auxiliary method information indicates that the operation process is executed by the user terminal; the auxiliary execution information of the operation process includes operation instructions for implementing the operation process; in step 603, the user terminal executes the auxiliary operation for the operation process according to the auxiliary execution information of the operation process, specifically, the user terminal executes the operation instructions in the auxiliary execution information of the operation process. By automatically executing the operation process according to the operation instructions by the user terminal, the efficiency of realizing the user's intention is improved, the risk of the user possibly performing incorrect operations is avoided, and thus the user experience is improved.

[0105] In some embodiments, in the operation instructions, the preceding sub-instruction adjacent to the target operation step is a confirmation instruction. The target operation step is the step that requires user authorization to perform the target operation on user data. The confirmation instruction is used to prompt the user to confirm whether they authorize the execution of the target operation before executing the target operation step. When executing operation instructions in the auxiliary execution information of the operation flow, the confirmation instruction can be executed before executing the sub-instruction corresponding to the target operation step to display a confirmation component. If the confirmation component receives confirmation information submitted by the user, the sub-instruction corresponding to the target operation step is executed; if the confirmation component receives cancellation information submitted by the user, the execution of the operation instruction is stopped. By executing the confirmation instruction, users can be provided with an interactive opportunity to verify whether the operation intent and operation flow match, reducing errors, improving the security of user data, and enhancing the user experience.

[0106] In some embodiments, the auxiliary method information indicates guidance for the user to perform an operation process; the auxiliary execution information of the operation process includes operation guidance information, which is used to guide the user to perform the operation process; according to the auxiliary execution information of the operation process, auxiliary operations are performed for the operation process, including: displaying the operation guidance information. By generating operation guidance information to guide the user, the efficiency of the user's use of the client can be improved, and the user experience can be enriched through guidance of different types of multimedia, and the user's research time can be reduced.

[0107] In some embodiments, the auxiliary information represents guidance for the user to execute an operation process through a question-and-answer interaction. The auxiliary execution information includes response text generated by a preset model based on the user's operational intent. The user then performs auxiliary operations related to the operation process based on this information, including displaying the response text. This question-and-answer interaction allows for more timely responses to users. Users can gradually adjust their questions based on the preset model's responses, thus expressing their intent more accurately and quickly. The question-and-answer interaction allows for real-time dynamic interaction between the user and the preset model. Users can ask questions as needed during the operation, enabling more precise resolution of specific user problems.

[0108] In some embodiments, before sending user operation intent information to the server, the client can acquire behavioral feature data, which represents the behavioral characteristics of the user's interactive operation; send the behavioral feature data to the server; receive and display a prompt message from the server when the behavioral feature data exceeds a preset threshold, the prompt message prompting the user to input operation intent information. By monitoring the user's behavioral feature data and automatically prompting the user to input operation intent information when it exceeds a preset threshold, the timeliness of technical support is improved, users feel personalized attention, and the user experience is enhanced.

[0109] The operation assistance method provided in the embodiments of this application will be described below with reference to a specific application scenario.

[0110] The operation assistance method provided in this application is applied to a system for managing cloud products and cloud services. This system includes a cloud server and a cloud product console. The cloud product console is the user interface, used to provide users with an interface for managing and configuring cloud products. The cloud server is used to process the cloud products and cloud services according to the user's management and configuration operations on the cloud product console.

[0111] In the cloud product console interface, a floating icon of an intelligent console tool is displayed. Based on the embodiments of this application, the intelligent console tool provides an operation assistance method for the user end, offering intelligent navigation and assisted operation functions to facilitate user familiarity with and use of the cloud product console. The intelligent console tool adopts the architecture of the GPT series model and is pre-trained based on a training dataset. The training dataset may include: product and technical documents, screenshots of various operations on the cloud product console, video recordings of various operations on the cloud product console, etc. Images or videos in the training dataset can be annotated using image annotation tools to identify the specific location of each button and control. Then, based on the sequence of screenshots or the sequence of image frames in the video, the operation objects of each operation step in the operation process can be determined in the interface. Optionally, data augmentation can be performed on the original training data as needed, for example, by rotating, scaling, or color processing images to expand the amount of training data, increase its diversity, and improve the generalization ability of the artificial intelligence model. In this way, by training the model with various operational knowledge information, and intelligently recognizing the web interface design graphics of the cloud product console, the model can learn the operation process of the cloud product console.

[0112] The intelligent console tool integrates three major AI-driven functions: an AI question-and-answer system, an AI navigation assistant, and AI operation assistance. Users can choose which function to use for assistance, and have the right to select the assistance method. The AI ​​question-and-answer system provides assistance through question-and-answer interaction. The AI ​​navigation assistant guides users through methods such as video guidance and visual interface guidance, prompting them with the next step of the operation process. The AI ​​operation assistance can automatically execute the user's required operation process. Users only need to enter a description and press the Enter key, and the intelligent console tool will begin the operation. Based on the user's description, the intelligent console tool can automatically execute a complete operation process. For example, taking the requirement of "purchasing a cloud product instance" as an example, the user opens the cloud service console and enters "purchase a 4c8g ECS" through the intelligent console tool, indicating that the user wants to purchase a four-core 8GB cloud server instance. The intelligent console tool can automatically execute the entire purchase operation process, including configuring parameters and clicking the purchase button, based on the user's required product parameters.

[0113] refer to Figure 8 The user's process of using the intelligent console tool may include the following steps:

[0114] Step 801: The user enters the cloud product console configured with the intelligent console tool.

[0115] Step 802: If users encounter operational problems while operating and managing cloud products, they can select the required assistance method from the three auxiliary functions provided by the intelligent console tool.

[0116] Step 803: The user enters a description of their intended operation into the intelligent console tool.

[0117] Step 8041: If the question-and-answer system is selected in step 802, users can ask questions at any time during the use of the cloud product console and get answers from the question-and-answer system.

[0118] Step 8042: Determine whether the answer can resolve the user's operational problem.

[0119] Step 8043: If not, the intelligent console tool can guide the user to view the product documentation.

[0120] Step 8044: Determine whether the product documentation can resolve the user's operational issues.

[0121] If the user's operation problem still cannot be resolved in step 8045, a work order can be submitted.

[0122] Step 8046: Technical support staff answer your questions.

[0123] Step 8047: If steps 8042 and 8044 determine that the problem can be solved, the user can perform configuration and management operations on the cloud product.

[0124] Step 805: If the navigation assistant was selected in step 802, then guidance information to assist the user can be displayed.

[0125] Step 8061: If step 802 selects auxiliary operation, first determine whether auxiliary operation is possible. If not, proceed to step 805 to display guidance information. If yes, proceed to step 8062.

[0126] Step 8062: Based on the pre-learned operational knowledge information, generate operation instructions and automatically execute the instructions to complete the operation.

[0127] Step 8063: During the execution of the instruction, determine whether there is a target operation.

[0128] Step 8064: If there is a target operation, user confirmation is required. If the user confirms, or if there is no target operation, proceed to step 8065 to continue executing the operation instruction. Otherwise, proceed to step 8066 to stop executing the operation instruction.

[0129] The intelligent environment built upon these features understands user needs and provides personalized assistance through artificial intelligence, offering precise operational instructions and Q&A solutions tailored to individual user requirements. Users no longer need to rely on cumbersome product documentation or wait for technical support; the intelligent control panel tool can respond and handle most user issues promptly. When a user is dissatisfied with the answer, they can ask the question again, or the intelligent control panel tool can guide them to use other forms of assistance. In special circumstances, when the intelligent control panel tool cannot provide a satisfactory answer, it can guide the user to consult relevant product documentation or contact technical support.

[0130] The intelligent console tool system includes a user-side intelligent console tool and server-side support for the user. The system primarily comprises five modules: a user input module, a knowledge graph module, an intelligent decision-making module, an operation generation module, and an output module. The user input module, located on the user's end, receives and analyzes user input in natural language or operational parameters. The knowledge graph module constructs a knowledge graph, organizing operational knowledge information, such as knowledge and rules from product and technical documents, into a complete knowledge system. The intelligent decision-making module applies artificial intelligence technology to learn from the operational habits and needs of a large number of users, providing more intelligent and personalized operational guidance for each individual user. The operation generation module generates corresponding operation instructions and steps based on the user's intent and needs, providing one-click navigation and automated task processing. The output module outputs the generated operation instructions and steps through the user's end, providing operational assistance.

[0131] Intelligent console tools can provide a user-friendly interface through interactive design, maximizing user efficiency. For example, when a user wants to purchase a specific cloud product, the intelligent console tool allows them to input their specific needs, such as "purchase a 3-month, annual / monthly subscription of type A in a certain city." In response, the intelligent console tool automatically executes a series of actions: from activating the "Create Instance" button, to navigating to the purchase page, and then selecting the product corresponding to the user's described specifications and duration. Throughout the process, the intelligent console tool ensures the accuracy of the user's selection and requests confirmation when necessary, especially when sensitive information such as payment is involved. If the user's description is unclear or the request cannot be fulfilled, the intelligent console tool intelligently suggests the closest option, highlights the suggestion on the user interface, explains why the purchase is not possible, and proactively provides alternatives.

[0132] Intelligent console tools learn from product and technical documentation and recognize the page design graphics of cloud product consoles. They provide users with one-click navigation and AI-assisted operation, answering user questions and assisting in completing all product functions. This significantly lowers the barrier to entry and streamlines workflows, improving customer onboarding efficiency. Intelligent console tools simplify user interaction, enabling both new and experienced users to easily master product functions and accelerating learning and application. They also significantly reduce reliance on technical support teams, lowering customer support costs. Furthermore, they enhance user experience, quickly helping users overcome problems when using emerging cloud services. Intelligent console tools require no coding; users only need to describe their needs and problems, greatly simplifying the user experience, lowering the barrier to entry, and accelerating user onboarding and proficiency. This allows users to focus on innovation rather than tedious management activities. This not only aids product promotion but also stabilizes and expands the customer base by increasing user satisfaction, significantly reducing operating costs and improving productivity.

[0133] Some embodiments of this application also provide an operation assistance device corresponding to the operation assistance method applied to the server provided in the foregoing embodiments. The operation assistance device is applied to the server and can be used to execute the operation assistance method. For the parts of the operation assistance device provided in this embodiment that are not described in detail, please refer to the relevant description in the operation assistance method.

[0134] like Figure 9 As shown in the figure, an operation assistance device for a server provided in this application embodiment includes an acquisition unit 901, a generation unit 902, and a sending unit 903.

[0135] The acquisition unit 901 is used to acquire operation intent information provided by the user terminal; the operation intent information is used to represent the user's operation intent on the target digital product.

[0136] The generation unit 902 is used to generate auxiliary execution information of the operation process based on the operation intention information and using a preset model; the operation process is used to realize the operation intention; the preset model is obtained by training an artificial intelligence model using operation knowledge information; the operation knowledge information is used to describe the operation process of each operation that can be performed on the target digital product.

[0137] The sending unit 903 is used to send auxiliary execution information of the operation process to the user terminal.

[0138] In some implementations, the generation unit 902 may include an acquisition subunit and a generation subunit. The acquisition subunit is used to acquire the user-selected assistance method information from the operation intent information, whereby the assistance method information represents the assistance method for the operation process; the generation subunit is used to generate assistance execution information corresponding to the assistance method information using a preset model based on the operation intent information.

[0139] In some implementations, the auxiliary method information indicates that the operation process is executed by the user terminal; the generation subunit can also be specifically used to: generate operation instructions for implementing the operation process using a preset model based on the operation intention information; and use the operation instructions as auxiliary execution information for the operation process.

[0140] Furthermore, in some embodiments, the operation instructions include sub-instructions corresponding to each operation step in the operation process, and the sub-instructions are arranged according to the order of each operation step in the operation process; the device may also include a determining sub-unit and an adding sub-unit; the determining sub-unit is used to determine whether a target operation step exists in the operation process using a preset model, and the target operation step is a step that requires user authorization to perform a target operation on user data; the adding sub-unit is used to add a confirmation instruction between the sub-instruction corresponding to the target operation step and the adjacent previous sub-instruction in the operation instructions when a target operation step exists, and the confirmation instruction is used to prompt the user to confirm whether to authorize the execution of the target operation before executing the target operation step.

[0141] In other embodiments, the auxiliary method information indicates guidance for the user to perform the operation process; the generation subunit may also be specifically used to: generate operation guidance information using a preset model based on the operation intention information, the operation guidance information being used to guide the user to perform the operation process; and use the operation guidance information as auxiliary execution information for the operation process.

[0142] In some other implementations, the auxiliary method information indicates that the user is guided to perform the operation process in a question-and-answer interaction manner. The generation sub-unit can also be specifically used to: determine the user's operation question based on the operation intention information; generate the answer text corresponding to the operation question using a preset model; and use the answer text as auxiliary execution information for the operation process.

[0143] In some embodiments, the acquisition unit 901 can also be used to acquire user operation behavior information within a preset time period provided by the user terminal before acquiring operation intent information provided by the user terminal; the sending unit 903 can also be used to send a prompt message to the user terminal when the operation behavior information matches preset behavior characteristics, wherein the preset behavior characteristics indicate that the user needs assistance with auxiliary execution information of the operation process, and the prompt message is used to prompt the user to input operation intent information.

[0144] In some embodiments, the acquisition unit 901 can also be used to acquire a training dataset before generating auxiliary execution information using a preset model. The training dataset includes at least one of multimedia information, knowledge graph information, explanatory documents, and historical operation information. The device can also include a training unit for training an artificial intelligence model using the training dataset to obtain a preset model. The multimedia information includes records of operations performed on the user's interface. The knowledge graph information is used to characterize the relationship between each operation and the user's interface features. The explanatory documents are used to describe the target digital product. The historical operation information includes information on historical operations performed by different users on the target digital product.

[0145] Some embodiments of this application also provide an operation assistance device corresponding to the operation assistance method applied to a user terminal provided in the foregoing embodiments. This operation assistance device is applied to a user terminal and can be used to execute the operation assistance method. For the parts of the operation assistance device provided in this embodiment that are not described in detail, please refer to the relevant description in the operation assistance method.

[0146] like Figure 10 As shown in the figure, an operation assistance device for user terminals provided in this application embodiment includes a sending unit 1001, a receiving unit 1002 and an execution unit 1003.

[0147] The sending unit 1001 is used to send the user's operation intention information to the server; the operation intention information is used to represent the user's operation intention on the target digital product.

[0148] The receiving unit 1002 is used to receive auxiliary execution information of the operation process returned by the server. The auxiliary execution information of the operation process is generated by the server using a preset model based on the operation intent information. The operation process is used to realize the operation intent. The preset model is obtained by training an artificial intelligence model using operation knowledge information. The operation knowledge information includes operation processes that describe the various operations that can be performed on the target digital product.

[0149] The execution unit 1003 is used to perform auxiliary operations for the operation process based on the auxiliary execution information of the operation process.

[0150] In some embodiments, the device may further include a detection unit, a display unit, and a generation unit; the detection unit is used to detect the triggering event of the operation assistance component in the current interface before sending the user's operation intent information to the server; the display unit is used to display multiple selection components, each selection component corresponding to different assistance method information, the assistance method information indicating the assistance method for the operation process; the detection unit is also used to detect the triggered selection component; the receiving unit 1002 may also be used to receive intent description information submitted by the user, the intent description information describing the operation intent; the generation unit is used to generate operation intent information based on the intent description information and the assistance method information corresponding to the triggered selection component.

[0151] In some implementations, the auxiliary method information indicates that the operation process is executed by the user terminal; the auxiliary execution information of the operation process includes operation instructions for implementing the operation process; the execution unit 1003 can be specifically used to execute the operation instructions in the auxiliary execution information of the operation process.

[0152] In some implementations, the preceding sub-instruction adjacent to the target operation step in the operation instruction is a confirmation instruction. The target operation step is a step that requires user authorization to perform the target operation on user data. The confirmation instruction is used to prompt the user to confirm whether to authorize the execution of the target operation before executing the target operation step. The execution unit 1003 can also be specifically used to: execute the confirmation instruction before executing the sub-instruction corresponding to the target operation step to display the confirmation component; if the confirmation component receives confirmation information submitted by the user, then execute the sub-instruction corresponding to the target operation step; if the confirmation component receives cancellation information submitted by the user, then stop executing the operation instruction.

[0153] In other embodiments, the auxiliary method information indicates guidance for the user to perform the operation process; the auxiliary execution information of the operation process includes operation guidance information, which is used to guide the user to perform the operation process; the execution unit 1003 may be specifically used to: display the operation guidance information.

[0154] In some other implementations, the auxiliary method information indicates that the user is guided to perform the operation process in a question-and-answer interaction manner. The auxiliary execution information of the operation process includes the answer text generated by the preset model according to the operation intention information. The execution unit 1003 can be specifically used to: display the answer text.

[0155] In some embodiments, the device may further include an acquisition unit, which is configured to acquire behavioral feature data before sending user operation intent information to the server. The behavioral feature data is used to represent the behavioral features of the interactive operation performed by the user. The sending unit 1001 is further configured to send the behavioral feature data to the server. The receiving unit 1002 is further configured to receive a prompt message from the server when the behavioral feature data exceeds a preset threshold. The prompt message is used to prompt the user to input operation intent information. The device may further include a display unit, which is configured to display the prompt message returned by the server.

[0156] The operation assistance device provided in this application embodiment can determine the user's operation intention for the target digital product by acquiring operation intention information provided by the user terminal. The server can generate auxiliary execution information for the operation process based on the operation intention information using a preset model. The user terminal can use the auxiliary execution information to assist the user in executing the operation process to achieve the user's operation intention. The preset model used by the server is obtained by training an artificial intelligence model based on operation knowledge information. The operation knowledge information used for training describes the operation process of each operation that can be performed on the target digital product. Therefore, the preset model can learn the operation process of each operation, thereby generating auxiliary execution information for the operation process that conforms to the user's operation intention based on understanding the user's operation intention. This application embodiment can provide customized technical support for users based on their individual operation intentions, reducing the intervention of human technical support and lowering the cost of technical support. Furthermore, by assisting users in executing the operation process through auxiliary execution information to achieve their operation intentions, it not only lowers the barrier to using digital products for users but also improves user efficiency and enhances the user experience.

[0157] Some embodiments of this application also provide an electronic device corresponding to the operation assistance method provided in any of the foregoing embodiments, for performing the above-described operation assistance method.

[0158] Figure 11 The present invention illustrates a hardware structure diagram of an electronic device according to an exemplary embodiment. The electronic device includes a communication interface 1101, a processor 1102, a memory 1103, and a bus 1104. The communication interface 1101, processor 1102, and memory 1103 communicate with each other via the bus 1104. The processor 1102 can execute the operation assistance method described above by reading and executing machine-executable instructions corresponding to the control logic of the operation assistance method in the memory 1103. The specific content of this method is described in the above embodiment and will not be repeated here.

[0159] The memory 1103 mentioned in this application can be any electronic, magnetic, optical, or other physical storage device, which can contain stored information such as executable instructions, data, etc. Specifically, the memory 1103 can be RAM (Random Access Memory), flash memory, storage drive (such as hard disk drive), any type of storage disk (such as optical disc, DVD, etc.), or similar storage media, or combinations thereof. Communication between the system network element and at least one other network element is achieved through at least one communication interface 1101 (which can be wired or wireless), which can use the Internet, wide area network, local area network, metropolitan area network, etc.

[0160] Bus 1104 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory 1103 is used to store programs, and the processor 1102 executes the programs after receiving execution instructions.

[0161] Processor 1102 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 1102 or by instructions in software form. The processor 1102 can be a general-purpose processor, including a network processor (NP), digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor.

[0162] The electronic devices provided in this application and the operation assistance methods provided in any embodiment of this application are based on the same inventive concept and have the same beneficial effects as the methods they employ, operate, or implement.

[0163] This application also provides a computer-readable storage medium corresponding to the operation assistance method provided in the foregoing embodiments, wherein a computer program is stored thereon, and the computer program, when run by a processor, executes the operation assistance method provided in any of the foregoing embodiments.

[0164] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical and magnetic storage media, which will not be elaborated here.

[0165] The computer-readable storage medium provided in the above embodiments of this application and the operation assistance method provided in the embodiments of this application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the applications stored therein.

[0166] This application also provides a computer program product corresponding to the operation assistance method provided in the foregoing embodiments, including a computer program that is executed by a processor to implement the method provided in any of the above embodiments.

[0167] The computer program products provided in the above embodiments of this application and the operation assistance methods provided in the embodiments of this application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the applications stored therein.

[0168] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0169] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0170] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

[0171] In this application specification and embodiments, any solutions involving the processing of personal information will be processed only under the premise of legality (such as obtaining the consent of the personal information subject, or being necessary for the performance of a contract), and will only be processed within the scope stipulated or agreed upon. A user's refusal to process personal information beyond that required for basic functions will not affect the user's use of basic functions.

Claims

1. An operation assistance method, characterized in that, The method is applied to the server side, and the method includes: Obtain operation intent information provided by the user terminal; the operation intent information is used to represent the user's operation intent on the target digital product; Based on the operation intent information, auxiliary execution information for the operation process is generated using a preset model; the operation process is used to realize the operation intent; the preset model is obtained by training an artificial intelligence model using operation knowledge information; the operation knowledge information is used to describe the operation process of each operation that can be performed on the target digital product; Send auxiliary execution information of the operation process to the user terminal.

2. The method according to claim 1, characterized in that, The step of generating auxiliary execution information for the operation process using a preset model based on the operation intent information includes: The user-selected assistance method information is obtained from the operation intent information, wherein the assistance method information represents the assistance method for the operation process; Based on the operation intent information, the auxiliary execution information corresponding to the auxiliary method information is generated using the preset model.

3. The method according to claim 2, characterized in that, The assistance method information indicates that the operation process is executed by the user terminal; the step of generating the assistance execution information corresponding to the assistance method information using the preset model based on the operation intent information includes: Based on the operation intent information, the preset model is used to generate operation instructions for implementing the operation process; The operation instructions are used as auxiliary execution information for the operation process.

4. The method according to claim 3, characterized in that, The operation instructions include sub-instructions corresponding to each operation step of the operation process, and each sub-instruction is arranged according to the order of the operation steps in the operation process. The method further includes: The preset model is used to determine whether there is a target operation step in the operation process. The target operation step is a step that requires the user's authorization to perform a target operation on the user data. If the target operation step exists, a confirmation instruction is added between the sub-instruction corresponding to the target operation step and the adjacent previous sub-instruction in the operation instruction. The confirmation instruction is used to prompt the user to confirm whether to authorize the execution of the target operation before executing the target operation step.

5. The method according to claim 2, characterized in that, The assistance method information indicates guidance for the user to perform the operation process; generating the assistance execution information corresponding to the assistance method information using the preset model based on the operation intent information includes: Based on the operation intent information, operation guidance information is generated using the preset model, and the operation guidance information is used to guide the user to perform the operation process. The operation guidance information is used as auxiliary execution information for the operation process.

6. The method according to claim 2, characterized in that, The assistance method information indicates that the user is guided to perform the operation process in a question-and-answer interaction manner. The step of generating the assistance execution information corresponding to the assistance method information using the preset model based on the operation intent information includes: Based on the operation intent information, determine the user's operation problem; The preset model is used to generate the answer text corresponding to the operation question; The response text is used as auxiliary execution information for the operation process.

7. The method according to any one of claims 1-6, characterized in that, Before obtaining the user's operational intent information, the method further includes: Obtain behavioral feature data provided by the user terminal, the behavioral feature data being used to represent the behavioral features of the interactive operations performed by the user; If the behavioral feature data exceeds a preset threshold, a prompt message is sent to the user terminal, which prompts the user to input the operation intention information.

8. The method according to any one of claims 1-6, characterized in that, Before generating auxiliary execution information for the operation process using a preset model, the method further includes: Obtain a training dataset, which includes at least one of multimedia information, knowledge graph information, explanatory documents, and historical operation information; The artificial intelligence model is trained using the training dataset to obtain the preset model; The multimedia information includes records of the operations performed on the user interface; the knowledge graph information is used to characterize the relationship between the operations and the user interface features; the documentation is used to describe the target digital product; and the historical operation information includes information on the historical operations performed by different users on the target digital product.

9. An operation assistance method, characterized in that, The method is applied to the user terminal and includes: Send the user's operation intent information to the server; the operation intent information is used to represent the user's operation intent on the target digital product; The system receives auxiliary execution information of the operation process returned by the server; the operation process is used to realize the operation intention; the auxiliary execution information of the operation process is generated by the server using a preset model based on the operation intention information; the preset model is obtained by training an artificial intelligence model using operation knowledge information; the operation knowledge information is used to describe the operation process of each operation that can be performed on the target digital product. Based on the auxiliary execution information of the operation process, perform auxiliary operations for the operation process.

10. The method according to claim 9, characterized in that, Before sending the user's operation intent information to the server, the method further includes: A trigger event of the operation assistance component in the current interface is detected, and multiple selection components are displayed. Each selection component corresponds to different assistance method information, and the assistance method information indicates the assistance method for the operation process. The triggered selection component was detected; The system receives intent description information submitted by the user, which describes the intent of the operation. The operation intent information is generated based on the intent description information and the assistance mode information corresponding to the triggered selection component.

11. The method according to claim 10, characterized in that, The auxiliary method information indicates that the operation process is executed by the user terminal; the auxiliary execution information of the operation process includes operation instructions for implementing the operation process; The step of performing auxiliary operations for the operation process based on the auxiliary execution information of the operation process includes: Execute the operation instructions in the auxiliary execution information.

12. The method according to claim 11, characterized in that, In the operation instructions, the preceding sub-instruction adjacent to the target operation step is a confirmation instruction. The target operation step is a step that requires the user's authorization to perform the target operation on the user data. The confirmation instruction is used to prompt the user to confirm whether to authorize the execution of the target operation before executing the target operation step. The execution of the operation instructions in the auxiliary execution information includes: Before executing the sub-instruction corresponding to the target operation step, execute the confirmation instruction to display the confirmation component; If the confirmation information submitted by the user is received through the confirmation component, the sub-instruction corresponding to the target operation step is executed. If the confirmation component receives a cancellation message submitted by the user, the execution of the operation instruction will be stopped.

13. The method according to claim 10, characterized in that, The assistance information indicates that the user is guided to perform the operation process; the assistance information for performing the operation process includes operation guidance information, which is used to guide the user to perform the operation process. The step of performing auxiliary operations for the operation process based on the auxiliary execution information of the operation process includes: The operation guidance information is displayed.

14. The method according to claim 10, characterized in that, The assistance method information indicates that the user is guided to perform the operation process in a question-and-answer interaction manner. The assistance execution information of the operation process includes the answer text generated by the preset model based on the operation intent information. The step of performing assistance operations for the operation process based on the assistance execution information of the operation process includes: The answer text is displayed.

15. The method according to any one of claims 9-14, characterized in that, Before sending the user's operation intent information to the server, the method further includes: Acquire behavioral feature data, which represents the behavioral characteristics of the interactive operations performed by the user; Send the behavioral feature data to the server; The system receives and displays a prompt message from the server when the behavioral feature data exceeds a preset threshold. The prompt message is used to prompt the user to input the operation intent information.

16. An operation assistance system, characterized in that, The system includes a cloud product console and a cloud server, wherein the cloud product console is used to provide an interface for managing cloud products; The cloud product console is used to obtain user's operation intent information for the cloud product through the interface, and send the operation intent information to the cloud server. The operation intent information is used to represent the user's operation intent for the cloud product. The cloud server is used to generate auxiliary execution information of the operation process using a preset model based on the operation intent information, and send the auxiliary execution information of the operation process to the cloud product console. The preset model is obtained by training an artificial intelligence model using operational knowledge information; the operational knowledge information is used to describe the operational process of each operation that can be performed on the cloud product. The cloud product console is used to receive auxiliary execution information for the operation process and to perform auxiliary operations for the operation process based on the auxiliary execution information.

17. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the program to implement the method as described in any one of claims 1-8 or 9-15.

18. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by a processor to implement the method as described in any one of claims 1-8 or 9-15.

19. A computer program product, comprising a computer program, characterized in that, The computer program is executed by a processor to implement the method according to any one of claims 1-8 or 9-15.

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