50 results about "Call duration" patented technology

An automated system and corresponding method is configured to predict a call duration of a customer service interaction between a caller and a customer-service agent of a call center, based at least in part on information provided orally by the caller to the automated system. The automated system transcribes the orally provided information, preprocesses the transcribed data, adds feature enrichment data to supplement the transcribed data, and executes a machine-learning model to predict the caller's intent. If the predicted caller's intent does not have an adequate confidence score associated therewith, the system requests additional data from the caller, and supplements the original data with newly provided data, and again determines a predicted call intent. This process may iterate until the confidence score satisfies applicable confidence criteria prior to utilizing two additional machine-learning models to predict a call duration of the interaction between the caller and a customer-service agent.

The invention relates to the technical field of artificial intelligence, and particularly discloses an artificial intelligence-based automatic identification method and system for fraud-related numbers, which breaks through the limitation that a traditional method depends on single-dimensional data through a data acquisition module, comprehensively describes a number behavior mode through multi-source data fusion, reduces erroneous judgment and missed judgment caused by one-sided data, and improves the identification accuracy of fraud-related numbers. A data foundation is laid for accurate identification; the feature library construction module introduces a knowledge graph technology, constructs the number, the associated object and the behavior event into a graph, and combines data cleaning and feature extraction and screening to form a dynamically updated fraud-related feature library; the method not only captures the surface behavior characteristics of the number, such as the call duration and the short message content, but also can mine the hidden fraud relation network to update the novel fraud characteristics in time, thereby solving the problem that the traditional method lags in the recognition of the complex fraud mode, and improving the timeliness and depth of the feature library.

The invention relates to the technical field of client intention pre-estimation, and discloses a client information management system, which comprises an information acquisition module used for acquiring interaction data of clients, and according to the login times, the page dwell time, the search times and the click behavior times of the clients acquired by official websites and mobile application channels, the client intention pre-estimation information is acquired by the information acquisition module; and obtaining a website score and an application score, and obtaining a customer service score according to the customer call times, the call duration and the work order recording times collected by a customer service system channel. According to the invention, clients are graded by using the intention score through the behavior analysis module, clients with low client activeness or recently paid clients are marked as low intention clients, high-intention clients really having continuous payment potential for products or services are effectively distinguished, and repeated investment of promotion resources into existing clients having satisfied consumption demands is avoided.

The embodiment of the invention provides a call quality detection method and device, electronic equipment and a storage medium, and is applied to the technical field of communication. The method provided by the embodiment of the invention is applied. The method comprises the following steps: acquiring a single call MOS value, a single call packet loss rate, single call average jitter, single call average delay, single call maximum jitter, a single call packet loss rate peak value, a single call codec type, a single call network type and a single call duration of each call of a user in a preset historical duration; and calculating the first data and constructing a user feature vector to obtain the user feature vector representing the call quality of the user. And respectively analyzing the feature vectors of the users through a K-means clustering algorithm and a DBSCAN clustering algorithm, identifying abnormal call users, and clustering the users, so that the users with the same or similar call quality are clustered in the same cluster. Therefore, the long-term call quality of the user is judged.

The invention discloses a multi-source data business travel service collaborative decision-making method and system, and relates to the technical field of business travel services, and the technical scheme is characterized in that the method comprises the steps: collecting business travel demand scene information of a current user, and calculating the resource matching complexity according to the business travel demand scene information; comparing and judging the resource matching complexity to obtain a first-level collaborative decision signal or a continuous analysis signal; if the resource matching complexity is compared and judged as a continuous analysis signal, extracting historical behavior data of the user, and constructing a resource relation model associated with the current scene according to the historical behavior data; analyzing calling time sequence characteristics of the user to the resource nodes based on the resource relation model; wherein the calling time sequence characteristic comprises an abnormal calling duration proportion and a continuous abnormal calling frequency; generating a time sequence exception index according to the exception call duration ratio and the continuous exception call frequency; the effect is that resources and service power can be flexibly allocated.

This application discloses a call method, apparatus, device, and medium. The method, applied to a server, includes: during a call between a calling party and a called party, if the calling party's first remaining call duration is less than a first threshold, sending multiple call processing options to the calling device; and upon receiving a target call processing option sent by the calling device, processing the current call based on the target call processing option, wherein the target call processing option is determined based on the calling device's response to the calling party's interactive operation regarding the multiple call processing options. In this way, the server can prevent the call from being suddenly interrupted by processing the current call when the calling party's first remaining call duration is less than the first threshold.

The invention provides a double-handle dispatching desk dialing display and control method and device and a storage medium, and the method comprises the steps: when a dispatching desk is started, loading a system configuration file and a handle drive program, detecting the connection state of at least two independent handles through a hardware interface, displaying a handle selection list on a main interface, and generating an adaptive layout for each handle icon; if dialing succeeds, information such as call duration and the number of the opposite side is displayed on a display screen of the first handle, functional keys such as on-hook and keeping are activated on the second handle, and if dialing fails, the display screen displays specific failure reasons and provides shortcut buttons for one-key redial and input emptying; through an interface layout optimization algorithm, high-frequency operation including dialing and mode switching is mapped to handle entity keys, interface level jump is reduced, a system automatically memorizes operation habits of a user, historical configuration is preloaded during next starting, and an operation path is shortened.

The design image is a vehicle information display interface showing call duration. 6.1) Image

The invention provides an information recommendation method and device, equipment, a storage medium and a program product, and the method comprises the steps: obtaining object association information and call moment information of a call object, the object association information comprises object attribute information and call information, and the call moment information comprises call moment information; the call information comprises a connection state, a call duration and an information recommendation record of the call object, and the call moment information comprises a first number of call moments; determining the call completing rate of the call object at the first number of call moments according to the object association information and the call moment information; determining the call moment of the call object according to the call completing rate of the first number of call moments; and recommending information to the calling object based on the calling moment of the calling object. According to the embodiment of the invention, the call completing rate of the call object and the accuracy of determining the call moment can be improved.

The invention provides a user risk assessment method and device, equipment, a medium and a product, and belongs to the technical field of communication security, and the method comprises the steps: obtaining historical risk data, historical communication behavior data, historical consumption behavior data and historical associated information data of a target user in response to a network access request of the target user; if the historical risk data represents that the target user is a non-risk user, performing feature extraction on the historical communication behavior data, the historical consumption behavior data and the historical associated information data; and inputting the obtained age, occupation, roaming place, package monthly fee, monthly average call duration, monthly average call times and monthly traffic usage amount of the target user into a pre-trained risk assessment model to obtain a risk coefficient output by the risk assessment model, and obtaining an assessment result of the target user according to the risk coefficient. According to the invention, risk assessment is carried out when the target user initiates the network access request, pre-assessment is realized, and risk users are prevented from implementing risk behaviors based on communication means.

To schedule a future interaction between a caller and a call-center, a management computing system associated with the call center is configured to determine an estimated call time for addressing the caller's issues, based at least in part on a predicted call intent as well as feature enrichment data received from one or more memory storage areas. Upon determining a predicted call duration for the call, the management computing entity accesses the caller's calendar, such as through an internet-based communication between the caller's user computing entity and the management computing entity, or via third-party access permissions provided by the caller. The management computing entity identifies one or more candidate timeslots based at least in part on the predicted call duration, and receives user input selecting a candidate timeslot for scheduling the callback.

The invention relates to the technical field of voice gateway detection, in particular to a voice gateway device detection method and system, and the method comprises the steps: obtaining a calling number, a called number, call duration and a calling location area code of each call; acquiring the calling frequency of each call number; acquiring a calling call abnormal value of each call number according to the calling position change and the call duration of each call number; acquiring a malicious call weight between the single called number and the single calling number, and further acquiring a malicious call suspicion value of each call number; acquiring a malicious call score of each call number, and dividing the call numbers into an abnormal call number, a normal call number and a risk call number; obtaining potential risk increments of the abnormal call number, the normal call number and the risk call number; and classifying the call numbers, and detecting call numbers with malicious call behaviors. According to the invention, the call number is evaluated from multiple dimensions, and the detection precision of the malicious call behavior is improved.

The invention discloses an outbound call forwarding method and system for realizing segmented manual forwarding, and relates to the technical field of call centers. The method comprises the following steps: acquiring service processing information of each manual transfer service in a historical time period and current appeal information of a target user, wherein the service processing information comprises at least one of call duration, question type, question content, docking customer service and satisfaction score; based on the service processing information of each manual transfer service in the historical time period, determining the capability expression degree of each customer service; based on the current appeal information and each ability expression degree, respectively determining a first adaptation degree between each customer service and the target user; and based on the first adaptation degree between each customer service and the target user, performing customer service allocation on the target user. According to the invention, the distribution accuracy of the manual customer service can be improved.

The invention discloses a data processing method and device, equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence. Obtaining service session data; determining N service links and starting and ending time of each service link through a large language model according to the service session data; according to the starting and ending time of each service link, determining a time-consuming service link in the N service links, the service duration of the time-consuming service link being greater than or equal to a preset service duration; according to stage session data corresponding to the time-consuming service link in the service session data, time-consuming root cause data is determined, and the time-consuming root cause data comprises at least one of the following items: a specialist factor and a non-specialist factor. Therefore, the problems that traditional manual analysis depends on experience judgment and the root cause is fuzzy are effectively solved, and accurate positioning and root cause tracing of the customer service call duration problem can be realized through intelligent analysis of the service session data by the large language model, so that the requirements of improving the service efficiency and the service quality are met.

This invention discloses an intelligent emergency call method and system, applicable to any user group in an emergency situation, including the elderly, women living alone, and patients with chronic diseases. It can run on various smart terminals such as smartphones, smartwatches, and smart bracelets. After a user triggers the call with one click, the system uses a multi-round cyclic dialing strategy to dial multiple emergency contacts sequentially, with subsequent rounds only dialing those who did not answer. Accurate answer determination is achieved by obtaining the actual call duration (zero indicates no answer). Simultaneously, it automatically integrates the GPS reverse geocoding address with the user's health record into a structured emergency call notification message and sends it. The entire process includes voice guidance, and all interactive nodes employ a countdown default continuation mechanism to ensure the process is not interrupted due to user inability to operate. This invention solves the three major defects of existing technologies: slow response, frequent misjudgments, and incomplete information. The entire process is triggered with one click and executed automatically.

The present application relates to the technical field of data analysis, in particular to a kind of intelligent call data analysis and prediction method, comprising the following steps, through communication equipment extraction call information generation node sequence and weight matrix, sliding detection statistical compression degree score extraction sub-sequence, joint feature model assesses path type, scanning frequency sequence extracts event-driven time stamp generation behavior label, based on hidden Markov model prediction behavior evolution result.In the present application, by time series adjacency clustering, call events are integrated into path node sequence, normalized call duration is generated weight distribution, sliding three-node algorithm identifies high-frequency compressible sub-sequence, fuses node density path length change and weight concentration degree to construct joint discriminant model, classifies call path type, dynamic frequency variable window extracts frequency difference to enhance behavior recognition sensitivity, and hidden Markov model dynamically predicts call behavior evolution trend based on state transition probability.

The application relates to the technical field of information tracing, in particular to a data security sharing method and equipment of a cross-network exchange platform, which comprises the following steps: determining a first abnormal characteristic value based on the distribution of deviated characteristic values of external requests of all Span data under any service node in each time period; determining a second abnormal characteristic value based on the change trend of the calling duration of all Span data under any service node in each time period, and combining the first abnormal characteristic value to determine a sampling adjustment coefficient of any service node in each time period, so as to adjust the sampling rate of Span data under any service node in the next time period of each time period. The application solves the problem that abnormal data is easy to be missed in the traditional method by dynamically adjusting the link tracking sampling rate, and improves the efficiency and accuracy of fault positioning of the cross-network exchange platform.

The invention relates to the technical field of resource allocation, in particular to an office resource allocation method based on the Internet of Things, which comprises the following steps: acquiring a task flow and a resource calling record, identifying a task dependence flow, extracting a resource type, a use time period and calling frequency, constructing a resource demand structure list, calculating resource occupation, and marking a high occupation flow. Generating a conflict area list, screening high-conflict requests, executing resource rearrangement, correcting calling duration, and generating allocation information. According to the method, the resource demand distribution structure is constructed by extracting the resource type, the use time period and the calling frequency in the task process, the resource allocation conflict area is identified, the combined screening is executed, the resource calling urgency degree is calculated in combination with the task priority and the resource utilization rate, and the high-conflict request starting point is effectively positioned; by eliminating the calling records with long resource idle period and low task level, the reasonability of task scheduling and the stability of office resource supply are enhanced.

Disclosed in the present application is a video call processing method. The video call processing method is applied to a cloud album server, and comprises: acquiring scene characteristic information of a first client that is sent by the first client; searching a cloud album for a target scene image, which matches the scene characteristic information and a possible call duration of a video call; generating an image video stream on the basis of the target scene image; and sending the image video stream to a video stream receiving end, such that the video stream receiving end replaces the video stream, which is sent to a second client, with the image video stream, and the video stream receiving end comprises at least one of an instant messaging server and the first client.

The invention relates to the technical field of user portraying, and discloses a user portraying method and system based on call interaction behaviors. The system comprises a call data acquisition module, a behavior feature extraction module, a user portrait construction module, a collection strategy generation module and a strategy execution feedback module. The call data acquisition module acquires metadata such as call recording data and call duration in real time; a behavior feature extraction module extracts interactive behavior features of dimensions such as tone intensity, response speed and language content tendency; the user portrait construction module continuously updates a user portrait label set according to the dynamic characteristics; the collection strategy generation module formulates adaptive personalized collection strategies for users with different characteristics in combination with the updated label set; when the strategy execution feedback module executes the strategy, effect data such as user repayment response and communication adaptability are synchronously collected. According to the system, through full-process closed-loop operation, the collection business process is optimized, and the user portrait accuracy and the collection strategy pertinence are improved.

The embodiment of the invention provides a call center capacity evaluation method, a call center capacity evaluation device and related equipment. In the embodiment of the invention, the maximum audio concurrency support capability of a single server and the resource consumption ratio of video to audio can be obtained, and the video traffic proportion of a call center and the call duration ratio of the video to the audio can be obtained; determining the maximum concurrency support capability of a single server under the mixed telephone traffic through a first calculation model, and predicting the total concurrency demand of the call center under the mixed telephone traffic through a second calculation model according to the number of calls per second, the audio call duration, the video telephone traffic proportion and the call duration proportion of the call center; and based on the total concurrency demand and the maximum concurrency support capability of the single server under the mixed telephone traffic, determining a preliminary server demand quantity of the call center, and based on the performance difference correction factor, correcting the preliminary server demand quantity to obtain the corrected server demand quantity of the call center.

The invention discloses a data center operation temperature monitoring method and a monitoring system, relates to the technical field of temperature monitoring, is used for solving the problem of abnormal temperature misjudgment caused by temperature adaptive change of the same data center in different positions, and is used for identifying a device combination participating in data storage in the data center and extracting device storage and temperature information. Screening core equipment, collecting the temperature of the core equipment, calculating the overall trend temperature of the equipment combination in combination with the temperature, the operation storage proportion and the calling duration of each marked equipment, extracting the operation temperature characteristic of the current period by utilizing principal component analysis, calculating the temperature time sequence deviation based on a sliding time window, and meanwhile, calculating the temperature time sequence deviation. The method comprises the following steps: acquiring ectopic data of the same equipment combination under different coordinates, constructing an ectopic temperature characteristic model, calculating a temperature bit sequence deviation between a current coordinate and an ectopic characteristic mean value, finally fusing the temperature sequence deviation and the temperature bit sequence deviation to predict the probability of temperature anomaly of a target coordinate in future time, and judging whether to trigger early warning.

The present application relates to the field of voice gateway detection technology, and specifically to a detection method and system for a voice gateway device, the method comprising: obtaining the calling number, called number, call duration, and calling location area code of each call; obtaining the calling frequency of each call number; obtaining the calling call abnormality value of each call number based on the calling location change and call duration of each call number; obtaining the malicious call weight between a single called number and a single calling number, and then obtaining the malicious call suspicion value of each call number; obtaining the malicious call score of each call number, and then dividing the call numbers into abnormal call numbers, normal call numbers, and risky call numbers; obtaining the potential risk increment of abnormal call numbers, normal call numbers, and risky call numbers; classifying each call number and detecting call numbers with malicious call behavior. The present application evaluates call numbers from multiple dimensions, thereby improving the detection accuracy of malicious call behavior.

The application belongs to the technical field of access control management, and discloses an entrance access control management method, device and equipment. The method comprises the following steps: collecting and identifying the identity information of a person passing through; determining target inspection items of the person passing through; determining the optimal inspection order based on the calling duration corresponding to each target inspection item; determining the target inspection item with the longest calling duration based on the optimal inspection order; preferentially initiating an inspection request of the target inspection item with the longest calling duration; sequentially calling other target inspection items in the optimal inspection order while waiting for the inspection result of the target inspection item with the longest calling duration; and determining the permission inspection of the person passing through after receiving the inspection results of all the target inspection items. The device comprises an identity identification module, an item determination module, an ordering module, a calling module and a determination module. The application optimizes the determination strategy of the inspection items and dynamically adjusts the inspection strategy, thereby improving the access control efficiency.

The invention provides a call interface interception method and device, equipment and a storage medium, and the method comprises the steps: determining a plurality of call interfaces corresponding to an interactive voice response system, determining the call frequency, call duration, interface failure rate and interface timeout rate of each call interface at a specified time, and carrying out the call of the call interfaces. According to the calling times, the calling duration, the interface failure rate and the interface timeout rate, calculating a comprehensive score of each calling interface, and according to the comprehensive scores, intercepting the calling interfaces, according to the method, the comprehensive score of the calling interface is determined by automatically utilizing the indexes of the calling frequency, the calling duration, the interface failure rate and the interface timeout rate so as to intercept the calling interface, the calling interface which consumes time and occupies resources is intercepted in time, and the situation that the interactive voice response system is stuck or unavailable is avoided.

The invention discloses an ETC service function code optimization suggestion method, device, equipment, medium and product, and relates to the technical field of service system operation and maintenance. The method comprises the following steps: firstly, aiming at a target service function in an ETC service system, extracting corresponding calling time consumption of each time from a service function calling time consumption record of a current latest sampling period, and then respectively quantifying a deterioration trend index value and a fluctuation characteristic index value of the target service function by introducing mathematical concepts such as a standard deviation and a slope; and finally, according to a comparison result of the index values and a preset threshold value, determining whether the target business function has a code optimization demand, and giving an optimization suggestion when the code optimization demand exists, so that the optimization space of the business function can be automatically found in the production operation of the ECT business system, and the production efficiency is improved. And a system operator and a development unit can complete development management and operation and maintenance management of rapid iteration in a time-saving and labor-saving manner, and practical application and popularization are facilitated.

The invention relates to the technical field of information tracing, in particular to a data security sharing method and device for a cross-network exchange platform, and the method comprises the steps: determining a first abnormal feature value based on the distribution of deviation feature values of external requests to which all Span data belongs under any service node in each time period; determining a second abnormal characteristic value based on the change trend of the calling duration of all Span data under any service node in each time period, and determining a sampling adjustment coefficient of any service node in each time period in combination with the first abnormal characteristic value, and adjusting the sampling rate of the Span data under any service node in the next time period of each time period. According to the method, the link tracking sampling rate is dynamically adjusted, so that the problem that abnormal data is easy to omit in a traditional method is solved, and the fault positioning efficiency and accuracy of the cross-network switching platform are improved.

The invention relates to the technical field of customer relationship management, in particular to an edge-deployed customer loss prediction method and system based on machine learning, and the method comprises the following steps: obtaining historical behavior data, attribute data and service use record data of a target user, the data comprises but is not limited to communication frequency, call duration, internet traffic, bill amount, complaint record and package change information; the method has the beneficial effects that an integrated model (such as XGBoost and LightGBM) based on a gradient boosting decision tree is adopted, and nonlinear features and complex interaction relationships in customer churn behaviors can be effectively modeled. Compared with a traditional logistic regression model, the method has the advantage that the prediction precision on an actual operation data set is remarkably improved. Through K-fold cross validation and a regularization mechanism (such as L1 / L2 constraint), the volatility of the model in different time periods or different service scenes is remarkably reduced, and the robustness of data disturbance is improved.

The invention relates to a cloud network performance test method and device, and computer equipment. The method comprises the following steps: acquiring service call chain information of a service node in a cloud network; obtaining a calling edge weight between the service nodes based on the calling initiating information, the calling receiving information and the calling duration; constructing a calling matrix based on the service node and the calling edge weight, and constructing a service association graph based on the service node and the calling matrix; key nodes in the service nodes are obtained based on the service association graph, the initial operation load of the key nodes is obtained, and the initial operation capacity of the key nodes and the test operation load of the key nodes are obtained based on the initial operation load; dynamically adjusting the initial operation capacity based on the test operation load to obtain the adjusted operation capacity; and obtaining a performance value of the cloud network based on the initial operation capacity and the adjusted operation capacity.

The invention provides a predictive outbound call-to-artificial resource scheduling method and system, and belongs to the technical field of task scheduling. According to the method, through ringing duration box separation processing, the answering probability difference (for example, the answering rate of ringing 15S is remarkably higher than 2S) of different ringing duration stages can be quantified, and therefore the accuracy of calculating the predicted answering number at the next moment can be improved. In consideration of a non-linear relationship between emotional fluctuation and the hanging rate, for example, the hanging rate of a negative emotional call is higher than that of a positive call. Therefore, the system can dynamically capture the complex behavior pattern through cross analysis of the call duration interval and the emotion label, so that the prediction precision of predicting the on-hook number at the next moment can be effectively improved. And the number of idle seats at the next moment is accurately calculated through the dynamically predicted answering number and hang-up number, and the call-out task amount is dynamically adjusted, so that call discarding and queue congestion can be effectively avoided, and the user experience and the call-out efficiency are greatly optimized.