281 results about "Personalization service" patented technology

The invention discloses an intelligent class case retrieval method and system based on reinforcement learning self-feedback, and the method comprises the following steps: S1, constructing a multi-level semantic understanding framework, carrying out the semantic understanding of a query case through the multi-level semantic understanding framework, and generating a complete semantic representation; s2, carrying out multi-dimensional similarity calculation and sorting optimization on the query case and historical discriminants in the candidate case library; s3, constructing a dynamic user portrait and optimizing a recommendation strategy; and S4, establishing multiple rounds of dialogues and context awareness, and carrying out visual display and feedback mechanism optimization. According to the intelligent class case retrieval method and class case retrieval system based on reinforcement learning self-feedback, a more accurate, efficient and reliable law intelligent retrieval system is finally achieved, judicial practice requirements are met, and quantitative and measurable technical progress is achieved in the aspects of retrieval accuracy, sorting quality, personalized service, law adaptability and the like.

The invention discloses an intelligent customer service dialogue management method and system fused with multi-layer memory, and belongs to the technical field of computers, and the method obtains a three-dimensional context through multi-mode context awareness, achieves the dynamic scheduling of a memory system through a memory coordinator, and combines a dynamic construction mechanism of a service situation portrait, thereby achieving the intelligent customer service dialogue management. The problem that the response of the intelligent customer service system is not matched with the complex and dynamic service demand of the user due to the single situation awareness dimension and the rigid memory scheduling mechanism is effectively solved, and the adaptive personalized service response can be generated according to the real-time change of the dialogue situation.

The invention provides a driver personalized service recommendation method based on scene perception. The method comprises the following steps: S1, collecting multi-dimensional data; s2, scene perception and recognition; s3, constructing a driver portrait and dynamically updating the driver portrait; s4, the intelligent recommendation engine generates personalized services; and S5, real-time decision making and service pushing are carried out. According to the driver behavior, the vehicle state and the external environment, the driver portrait including the behavior characteristics, the preference characteristics and the risk level is formed, and accurate recommendation is carried out.

Provided are a personalized dynamic intent recognition method and apparatus, and a related device, related to the technical field of computers. The method comprises: acquiring historical dialog data of at least one user with customer service (S202); on the basis of the historical dialog data, constructing empirical tuple data for training a deep reinforcement learning model, the deep reinforcement learning model being used for predicting a value of an agent from one state to one action, the empirical tuple data comprising a current state, an action, a reward value, and a next state of the agent (S204); acquiring personalized weight information of each user, and, in the process of the agent training the deep reinforcement learning model by using the empirical tuple data, using the personalized weight information of each user to update a prediction value of the deep reinforcement learning model, until a personalized intent recognition model satisfying a preset condition is obtained. The present method can dynamically and accurately identify a personalized intent of a user, so as to more conveniently provide the user with a higher-quality personalized service.

The invention provides a system and method for enhancing long-term memory of a large language model, and relates to the technical field of artificial intelligence. The system solves the problems of memory loss, information confusion and the like in multiple rounds of dialogues through hierarchical memory storage, time-aware retrieval and an automatic reflection compression mechanism, improves response consistency and credibility, and supports personalized services and complex task scenes.

The invention relates to the technical field of attribute graph collection and release, in particular to an attribute graph collection and release method, system and device based on local differential privacy and a medium. Receiving disturbed data from each client; based on all disturbed data, estimating community division of the original graph structure and triangular counting of each node; obtaining a target graph structure based on community division and triangular counting; and on the basis of the target graph structure and the disturbed data, node attributes are optimized, so that node attribute distribution and community division are kept consistent, and a final publishable target attribute graph is obtained. The method has the advantages that strict requirements of local differential privacy are met on the privacy protection level, and multi-dimensional features such as a community structure, triangular counting and node attribute homogeneity are reserved in the published attribute graph at the same time; and the practical value of the synthetic data in applications such as downstream graph analysis, community discovery and personalized service is greatly improved.

The invention discloses a decentralized AI service credible management system and a decentralized AI service credible management method. According to the method, the client and the server of each network domain are constructed through the credible AI model based on federal learning, so that the credibility of the AI model obtained by training can be ensured; the block chain node in each network domain can evaluate the credibility of the AI model uploaded to the block chain by the server of each network domain through the AI model credibility evaluation based on logistic regression and clustering, thereby supporting the subsequent personalized AI service. Through on-chain registration, under-chain storage and authorization access control of the AI model realized based on the client, the server and the block chain network, block chain-based AI service management is realized, and decentralized management of the whole life cycle of the AI service can be realized.

The invention provides an information consultation method and system based on artificial intelligence, an electronic device and a storage medium, and aims to solve the problems that a telephone charge query system is complex in user interface, poor in interactivity and lack of personalized services, the method comprises the following steps: receiving a voice or text input by a user; recognizing a user intention in the voice or text through a pre-trained intention recognition model; according to the user intention, services and / or functions needing to be called are / is determined; calling services and / or functions needing to be called in a chain calling mode to obtain and process reply information, and integrating data returned by different services and / or functions to generate a unified response result; and displaying reply information to the user in one or more output forms according to the response result through multi-mode output. According to the invention, accurate user input analysis and intention recognition can be realized, intelligent decision can be made according to the user intention, related service processing information can be called, and information readability is enhanced through multi-modal output.

The invention provides a task processing method and device based on end-cloud collaboration, is applied to a multi-agent collaboration system based on end-cloud collaboration, and relates to the technical field of data processing. The method comprises the following steps: firstly, converting user input into a structured intention message, and decomposing the structured intention message into a directed acyclic graph task flow; then, based on task node requirements and agent state information, dynamically allocating agents on the end side or the cloud to execute corresponding tasks; in the execution process, maintaining a global context state tree and realizing incremental synchronization between end clouds; and finally, all task results are fused and fed back to the user. Dynamic decomposition and node-level fine-grained scheduling of the composite task are realized, and the task processing efficiency is improved; end cloud resource utilization is optimized, and invalid network requests are reduced; and through context increment synchronization, the accuracy of personalized services is improved, and the user experience is remarkably enhanced.

The invention is suitable for the technical field of smart home control, and provides a skill generation method, control equipment and a control system for an intelligent agent with a body. The method comprises the following steps: acquiring a first behavior sequence formed by interaction events of a user and smart home equipment in a first time period; performing multi-dimensional mining on the first behavior sequence, and mining a plurality of behavior modes; for any behavior mode, generating a corresponding skill package based on the behavior mode; and when a trigger source is detected, the intelligent agent controls the corresponding smart home equipment to execute corresponding actions according to the generated skill packages. According to the invention, behavior modes can be mined from multiple dimensions, complex behaviors can be understood, and self-adaptive smart home personalized services can be realized.

The invention discloses a voice control method and device for a household electrical appliance, and the method comprises the following steps: S1, collecting a user voice signal, and carrying out the preprocessing of the user voice signal; s2, performing local wake-up detection and local voice recognition on the preprocessed voice signal to obtain a text instruction; s3, performing complexity analysis on the text instruction; s4, based on the result of the complexity analysis, processing the text instruction through a local path or a cloud path to generate a control instruction; and S5, controlling the target household electrical appliance to execute corresponding operation according to the control instruction. According to the invention, the recognition efficiency and the recognition accuracy can be improved; the natural language expression of the user can be converted into accurate equipment linkage operation in combination with voice context information; a simple control instruction is subjected to localization processing, only necessary data are uploaded to the cloud, and the risk of privacy disclosure is reduced; personalized services are provided by binding voiceprint recognition with user preferences.

The invention discloses a multi-agent-based college entrance examination consultation method and system, and belongs to the technical field of large language model application. The problems that in the prior art, a traditional college entrance examination consultation system based on a large language model is limited in complex problem processing capacity, insufficient in personalized service capacity and lack of expert knowledge are solved. The method comprises the following steps: S1, constructing a local knowledge base containing objective data and expert knowledge extracted through a specific process; s2, designing a knowledge retrieval tool for accessing a network and a local knowledge base; s3, introducing a long-term memory mechanism to store, apply and update personalized information of the user in a cross-session manner; and S4, constructing a multi-agent collaborative architecture, analyzing user intentions according to user personalized information, scheduling expert agents, and integrating results to realize college entrance examination consultation. According to the method, the accuracy and comprehensiveness of answering are effectively improved, continuous personalized services are provided, and the method can be applied to online college entrance examination consultation.

The invention discloses an intelligent voice outbound system capable of realizing automatic adjustment, and relates to the technical field of intelligent voice interaction, the system comprises a voice acquisition and preprocessing module, a voiceprint analysis and emotion recognition module, a dynamic verbal skill generation module, a verbal skill real-time optimization module and a voice synthesis and outbound module; the communication efficiency and personalized service are improved through a'generation-optimization-feedback 'closed-loop design, the system generates scene-fitting verbal skills according to customer emotions, historical records and demands, adjusts strategies according to instant feedback of customers, reduces invalid conversations, reduces customer conflicts, shortens the communication period, and meanwhile, improves the user experience. Voiceprint features are decomposed into four quantifiable dimensions, emotion is accurately recognized in combination with a combination rule, limitation of a single index is avoided, the dynamic verbal skill generation module is based on a generative adversarial network, high-quality verbal skill can be learned, the dynamic verbal skill generation module adapts to multiple scenes, customization cost is reduced, and intelligent outbound large-scale application is promoted.

The invention discloses an intelligent interaction robot control system which comprises a sensing input module, a core processing module, an output execution module and a system management and maintenance module. The perception input module collects multi-modal data through a visual, auditory, environment and touch unit; the core processing module carries out fusion analysis on the data and generates a decision instruction through a multi-modal information fusion unit, a situation cognition and decision unit, an emotion calculation unit and a motion planning unit; the output execution module executes an interaction task through a voice unit, an expression action unit and a motion unit; and the system management and maintenance module provides knowledge base, cloud collaboration and energy monitoring support. Through multi-modal information deep fusion and situational cognition, accurate understanding of user intentions and environments is realized, emotional interaction and personalized service capabilities are provided, the problems that an existing system is single in interaction mode and lacks context understanding are solved, and the intelligent level and user experience of the robot are remarkably improved.

The application relates to the field of electronic equipment. The application provides a method for verifying the identity of a user. The method can be performed by a device for collecting identity information to be verified of a user and a device for verifying the identity information to be verified. The device for collecting the identity information to be verified or the device for verifying the identity information to be verified can determine a target identity verification mode suitable for a non-self device from multiple identity verification modes according to device information of the non-self device, so that the target user identity verification mode can be suitable for two different devices at the same time and can be more matched with a current scene, and personalized services can be provided for the user.

The invention discloses a cross-platform member unified management and service optimization system. A data fusion processing module breaks a data island, fuses multi-platform member data, and constructs a complete member portrait; the member value evaluation module comprehensively and accurately evaluates the member value by using a member value evaluation formula based on the comprehensive data, insights the contribution and potential of the member value, and provides a basis for a marketing strategy; the member layering module divides levels according to values and dynamic thresholds, enterprises can formulate personalized management strategies accordingly, resources are reasonably distributed, and the management efficiency and the member satisfaction degree are improved; the service recommendation module calculates and recommends personalized services according to a matching degree formula in combination with the hierarchy and historical behavior data; all the modules are tightly matched, a complete closed loop is formed from data integration, value evaluation, hierarchical division and service recommendation, the member experience is effectively improved, and the recognition sense and stickiness of members to enterprises are enhanced.

The invention relates to a personalized network guarantee service pushing method and device, equipment and a storage medium. The method comprises the steps that a specific scene where a user is located is recognized through a terminal side intention perception SDK, credibility verification is carried out, and the specific scene comprises at least one of access to a preset place network, poor network quality or starting of a high-network-demand application; based on a specific scene in which the user is located, obtaining signing state data of a current service of the user; comprehensively analyzing the user service demand and the network adaptation capability based on the signing state data of the current service of the user; formulating or updating a personalized QoS (Quality of Service) network guarantee strategy matched with the specific scene, or pushing a personalized network guarantee service ordering request to a user, and performing state feedback; and executing a network service guarantee operation according to the network guarantee strategy. By adopting the method, precise scene perception and network side multi-network element cooperation can be realized, and the reach rate and the order conversion rate of the network guarantee service are improved.

A system for continuously adapting a content on an education platform is described. The system includes a plurality of user devices, a personalization server communicatively coupled to the plurality of user devices, and an optimization server communicatively coupled to the personalization server. Each user device is configured to obtain data associated with a corresponding user. The personalization server creates learning pathways for each user. The optimization server generates content associated one or more education disciplines based on the learning pathways. The personalization server further determines performance data and interaction data based on the content and adapts the learning pathways based on the performance data and the interaction data. The optimization server receives the adapted learning pathways and updates the content based on the adapted learning pathways.

The invention discloses an intelligent education video service system based on cloud computing and a mobile terminal, and relates to the field of intelligent online education video services. Comprising a terminal and network module, a front-end processing module, a live broadcast and cooperation module, a test and evaluation module, a content generation module, a content auditing module, a cloud computing and resource management module and a data processing and personalized service module. According to the online education system, multiple substantive improvements are made in the aspects of a cooperation mode, an evaluation mechanism, content structured processing, dimension auditing and the like, obvious technical progress and creativity are achieved, the interactivity, fairness, safety and the intelligent level of the online education system can be remarkably improved, and through linkage of the timestamps and cooperation records, the online education system is more intellectualized. The live video is automatically split into scene segments, index playback, improper audio content identification and sound level audit improvement are facilitated, and students can quickly acquire aggregated content according to needs to form a structured review path.

The present invention relates to a consumer inner tendency typing analysis model production system and method using generative AI, and the present invention can automatically produce a consumer typing module that can classify consumer's inner tendencies into 256 types based on four tendency topics simply by inputting a client company's topic. Through this consumer typing module, the client company can provide customized customer services and customized marketing strategies for each consumer type, along with product recommendations and personalized services.

The present invention relates to a system of hands-free intelligent point of sale. The system (100) includes a computing device(102), a shopkeeper touch interface(108), and a customer touch interface(140), a camera(110), a customer microphone(112), a shopkeeper microphone(142), a first speaker(114), a second speaker(116), a networking device(118), a cloud server computer(120). The system(100) is being used as a point of sale that provides the shopkeeper with data analytics for sales, customers and inventory management. The camera(110) captures customer image and sends to the cloud server computer(120) through the computing device(102). The cloud server processor(124) recognize the customer in real time using machine learning models provides the personalized services, promotions and entertainment options to customer as per previous purchase. Simultaneously, the cloud server processor(124) provides the inventory data to the shopkeeper, so that shopkeeper is able to track inventory of particular items and order items from distributor through voice command using the shopkeeper microphone(142).

The application discloses a kind of based on plug-in AI digital person ability extension method, the method includes according to the data that user submits and interacts, extract user information feature matrix, construct user preliminary portrait;Based on user preliminary portrait, select relevant plug-in, pre-load plug-in and automatically select ability extension strategy;Initialize plug-in function, according to ability extension strategy and user dialogue system gradually enable plug-in, expand the ability of AI digital person, record enabled function information;According to enabled function information, construct AI digital person ability management system, output AI digital person ability matrix;Using the document uploaded by user, parse the task list of user, match ability matrix, customize user personalized task list.The application solves the flexibility and personalization problem of AI digital person function expansion under different user needs and scenarios, realizes the intelligent adaptation and ability improvement of AI digital person in diversified application scenarios, provides more accurate and efficient personalized service for user.

This invention provides a highway traffic spatiotemporal service platform and method based on multi-source heterogeneous data fusion. The platform includes: a data acquisition module; a data fusion management module; a base map creation module for generating a highway traffic spatiotemporal service base map with highway intersections as key nodes; a traffic situation analysis module for generating a traffic situation prediction map; and a decision support and personalized service module for providing real-time, visualized traffic situation displays, traffic guidance strategies, and personalized travel services to traffic managers and traffic participants based on the traffic situation prediction map. This invention not only provides real-time, visualized decision support for traffic managers but also allows for customized personalized travel plans for traffic participants, thereby achieving comprehensive perception and precise control of highway traffic operation status and greatly improving the level of intelligent traffic operation management.

The present invention relates to a system for producing a consumer inner disposition typing analysis model by using generative AI. The present invention may allow companies to customize production to be suitable for various customers by generating a final typing module including a question and answer set for consumer type classification according to disposition topics using generative AI and allow customer companies to establish customized customer services and customized marketing strategies for each consumer type and provide product recommendation and personalization services through a consumer typing module.

The embodiment of the invention discloses an intelligent old-age care monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of intelligent old-age care guardian.The method comprises the steps that physiological indexes are collected in real time through physiological monitoring equipment, environment data are monitored through an environment sensor, and behavior data are captured through a behavior capturing terminal; analyzing the environment data by using a time sequence clustering algorithm to obtain an environment abnormal value, analyzing the physiological indexes and the behavior data based on a Bi-LSTM model and an Attention model to obtain a behavior sequence, and calculating a physiological deviation value; analyzing the behavior data through MFCC feature extraction and a Transform model to obtain an emotion fluctuation value, and generating a comprehensive risk score; and carrying out risk grade division, carrying out data recording and monitoring when the risk is low, carrying out family member early warning when the risk is medium, and triggering an emergency response mechanism to carry out multi-device linkage when the risk is high. According to the invention, the problems of high false alarm rate, response lagging, lack of psychological monitoring and personalized service and weak privacy and security mechanism in the prior art are solved.

The invention relates to the field of user portraits, in particular to a customer personalized service system and method based on multi-modal data fusion, and the system comprises a multi-source data module, a feature vector module, a node label module, a task aggregation module and a service prediction module, the feature vector module is used for extracting user feature vectors, the node label module is used for capturing homogeneous nodes, the task aggregation module is used for clustering personalized label vectors, and the service prediction module is used for outputting a probability value of executing a current task by a client. The timeliness and integrity of the data are ensured, the user portrait precision and the recognition accuracy of the user portrait model are improved, accurate allocation and personalized prediction of customer resources are realized, the accuracy of customer personalized label classification is improved, and the precision of a customer personalized recommendation algorithm is ensured.

The application discloses a voice privacy data protection method and a storage medium, and the method comprises the following steps: deploying a trained feature separator, distributing the feature separator to a user end through an offline third-party model training module, and setting feature information to be protected by the user, wherein the feature separator selectively separates real voice data of the user according to the setting of the user, transmits feature information not containing privacy information separated to a voice server through a symmetric encryption mode, and then the voice server decrypts and analyzes the encrypted feature value after receiving the encrypted feature value, and pushes corresponding personalized services. The prior art usually protects the privacy of the user through a noise adding mode, and the result will affect the utility of the data. The application can provide multiple choices for the user, the user can customize a privacy protection strategy according to the demand of the user, and the designed feature separator separates voice data according to the setting of the user in the user end, so that the data can be shared under the condition of guaranteeing the data utility and the privacy.

The invention provides an intelligent pillow sleep monitoring and personalized improvement method based on digital twinning, relates to the technical field of medical health information, and aims to quickly judge a reflection condition and make emergency intervention through hard-wired logic, generate a personalized intervention strategy for execution by establishing a dynamic digital twinning body, and improve the sleep monitoring and personalized improvement of an intelligent pillow after each intervention. The method comprises the following steps: acquiring implicit physiological feedback data of a user to calculate an intervention consensus score, executing differentiated parameter updating based on the intervention consensus score, performing structural self-evolution when new feature data appears, removing and creating an internal characterization component, and through a dual mechanism of parameter updating and structural self-evolution, establishing an internal characterization component. According to the method, the dynamic change sleep portrait of the user can be accurately described by the digital twinborn body all the time, so that continuous, effective and more intimate personalized services are provided, the technical problem that the suitability of a static model is attenuated is fundamentally solved, the suitability with the user is improved, and a good intervention effect is ensured.

The invention relates to the technical field of intelligent transportation, and discloses a man-machine interaction autonomous vehicle passenger personalized information service system. A data capture module of the system divides data segments based on the occurrence time of an interaction event, and generates an interaction data set with aligned time sequences; a feature extraction module performs feature extraction on the interaction data set subjected to time sequence alignment to obtain a passenger behavior feature vector and a vehicle environment feature matrix; the graph neural network module inputs the feature vector and the feature matrix into a pre-trained graph neural network model, and outputs a service association graph; the random walk module applies a random walk algorithm on the service association map to generate a passenger preference path sequence; the dynamic adjustment module dynamically adjusts a service activation probability threshold according to the phase change of the real-time driving scene, and selects a service path of which the probability is higher than the threshold to generate a personalized service instruction; and the execution control module converts the personalized service instruction into an operation signal and controls the information output equipment to deliver the service.

The invention discloses an internet-based medical insurance service platform comprehensive intelligent management system, which relates to the technical field of medical insurance intelligent management and comprises a data receiving module, a portrait construction module, a strategy adaptation module, a compliance verification module and a service navigation module. The system performs heterogeneous feature co-processing on the user identity authentication sequence and the medical service application text to generate a user service demand portrait; performing rule matrix matching through a multi-level policy adaptation engine, and outputting a grading policy adaptation result containing matching degree distribution; based on the distribution, bidirectional compliance verification is carried out on the expense settlement document image and the medicine directory query log, and a medical insurance settlement compliance report is formed; and generating and pushing a personalized service navigation strategy. According to the invention, deep integrated description of user service requirements and dynamic accurate compliance review based on quantitative evaluation are realized.