195 results about "Virtual user" patented technology

An advanced AI system, known as Bayesian Graph-Based Retrieval-Augmented Generation with Synthetic Feedback Loop (BG-RAG-SFL), combines Bayesian evaluation, graph-based retrieval, and synthetic data feedback to create a continuously improving AI platform. The present invention integrates multiple LLMs, optimizing their performance while managing complexities across different models. Key features include a knowledge graph-based RAG system, a Bayesian evaluation network, a secondary ground-truth graph for verification, synthetic data generation for ongoing improvement, and a multi-agent verification system. The system also functions as an AI operating system capable of acting as a virtual user with screen I / O control and managing multiple computers as an intelligent process automation system.

An advanced AI system, known as Bayesian Graph-Based Retrieval-Augmented Generation with Synthetic Feedback Loop (BG-RAG-SFL), combines Bayesian evaluation, graph-based retrieval, and synthetic data feedback to create a continuously improving AI platform. The present invention integrates multiple LLMs, optimizing their performance while managing complexities across different models. Key features include a knowledge graph-based RAG system, a Bayesian evaluation network, a secondary ground-truth graph for verification, synthetic data generation for ongoing improvement, and a multi-agent verification system. The system also functions as an AI operating system capable of acting as a virtual user with screen I / O control and managing multiple computers as an intelligent process automation system.

A display improvement support method and device for improving a display in accordance with the user's conscious reaction is provided. [Solution] In the display object improvement support device, the generation AI control unit executes the following steps: a reaction prediction prompt generation step of generating a reaction prediction prompt that instructs the generation AI to predict the reaction that will occur in the mind of a virtual user having user profile information of at least one of age, sex, occupation, height, and weight when the virtual user uses the display object; a reaction acquisition step of inputting the reaction prediction prompt into the generation AI and acquiring reaction information, which is information related to the reaction, from the generation AI; a screen operation prediction prompt generation step of generating a screen operation prediction prompt that instructs the generation AI to predict the screen operations that the user will perform on the screen of an information device based on the reaction information; and a screen operation acquisition step of inputting the screen operation prediction prompt into the generation AI and acquiring screen operation information, which is information related to screen operations, from the generation AI.

Embodiments of the present disclosure provide a system for provide experience to real time feel of trail of actual clothes to a user is disclosed. The system is utilized in online as well as physical stores. The system utilizes a camera communicatively coupled with a body scanner. The system is further communicatively coupled with a mobile device for providing details of the user. The mobile device may transmit a trigger to a body scanner after receiving an input from the user. The input indicates selection of a cloth from a plurality of clothes available in the store. After receiving the trigger from the mobile device, the body scanner may initiate the camera and determine details of the user. The mobile device may overlap the selected cloth on to a dummy user created using the details of the user.

An Adaptive Tangible User Interface (ATUI) for use in an extended reality environment in which tangible interfaces are composed in real time based on identified affordances of existing objects in the physical environment and the input tasks of a user. An extended reality system can be provided with instructions executable by one or more processors to perform processing including: generating a representation of the real-world environment within a field of view of the user; identifying physical objects within the real-world environment; generating a set of possible performable gestures afforded by available object affordance factors; determining potential input tasks; composing performable gestures for the potential input tasks; and selecting a physical object for use as an adaptive tangible user interface. Techniques for designing a virtual user interface, overlaying the virtual user interface on a selected ATUI physical object, and maintaining alignment of the virtual user interface, are also provided.

The invention provides an intelligent agent training management method, system and device, and belongs to the technical field of intelligent agents, and the method specifically comprises the steps: taking an interaction demand type between a virtual user and an intelligent agent as a basis, combining the change conditions of interaction user data in different time periods, and carrying out the training management of the intelligent agent; determining an available interaction time period between the virtual object and the intelligent agent, and determining an analysis processing strategy of interaction data between the interaction user and the intelligent agent according to the data of the available interaction time period; according to the method, the interaction management strategy of the virtual object in the time period except the available interaction time period is determined according to the analysis processing result of the interaction data of the virtual object in the available interaction time period and the interaction data between the interaction user and the intelligent agent, so that the updating processing efficiency of the intelligent agent is improved, and meanwhile, the influence on a normal business process is also reduced.

The invention discloses an online health management method and system based on big data, and relates to the technical field of online health management, a virtual user executes a selected health service to simulate the process that a real virtual user participates in a health activity in actual life, and after the virtual user completes the health service, the virtual user can take part in the health activity. The pheromone concentration is updated according to the effect of the plan, the virtual user carries out selection and execution of the health care service and updating of the pheromone concentration according to the pheromone concentration and a heuristic rule, convergence is carried out after a preset number of iterations is achieved, natural attenuation of the pheromone concentration is simulated based on the volatilization rate of the pheromone concentration, and the health care service is obtained. After the last round of iteration is completed, according to the pheromone concentration and the health care service effect, the optimal health care service is selected as the final personalized recommendation. The management system effectively generates more personalized health and care services for the virtual users, progressive optimization helps the management system continuously adapt to health changes and demand evolution of the virtual users, and the long-term effectiveness of the health and care services is improved.

This document describes methods, devices, systems, and means for managing a virtual user equipment, UE, set by a network entity, the network entity registering multiple user equipment to the virtual UE set, generating a virtual-UE-set session context, and sending a virtual-UE-set context notification to a base station, directing the base station to transmit the virtual-UE-set session context to each of the multiple user equipment in the virtual UE set. The network entity determines that a first user equipment in the virtual UE set is in-focus for aa first instance of an application, applies a first set of capabilities associated with the first UE to a session for the first instance of the application, and based on the relaying, relays data between the first instance of the application and an application server based on the first set of capabilities.

A novel electronic system provides automated recognition, registration, and location tracking of physical, holographic, and / or virtual user items that can be visualized in a computer graphics-infused augmented-reality or mixed-reality environment with an electronic visualization device. The novel electronic system is also capable of executing intelligent machine valuation of user items and reflecting dynamic changes in valuation based on peer interests within the augmented-realty or mixed-reality environment. Each user item identified in the user's visual perspective through the electronic visualization device connected to the novel electronic system undergoes object extractions, class categorizations, and image segmentations by the novel electronic system to determine whether a particular item is substantive and worthy of location tracking, based on the item owner's preferences. The item is paired with related metadata and stored in a system database, and later retrieved by a search command in the augmented-reality or mixed-reality environment to display its known location.

The invention discloses an Internet of Things card intelligent management method and system based on multiple operators, and relates to the field of multi-operator network collaborative management, and the method comprises the steps: collecting network service quality data, a network state, a multi-operator network and an available bandwidth index, encrypting a device identifier and a service type, and transmitting the encrypted device identifier and service type to an intelligent management platform; distributing a virtual user identification module identity, and generating a terminal exclusive key; an operator trains a local long-short-term memory network quality prediction model based on local network data to obtain a model gradient, and encrypts the model gradient generated by terminal exclusive key training to obtain an encrypted model gradient; and performing decryption and aggregation calculation on the encryption model gradient through a security aggregation algorithm to generate global network quality prediction model parameters. According to the invention, through an innovative federal learning encryption gradient aggregation mechanism and a block chain intelligent settlement system, efficient collaborative management of the Internet of Things cards of multiple operators is realized.

The invention provides a virtual user simulation method and system for dialogue testing, and the method comprises the steps: obtaining a plurality of pieces of effective multi-round dialogue data from a to-be-tested system, and carrying out the multi-label labeling, so as to construct a basic sample data set containing user portrait labels, the key sample data set further comprises user emotion tags; constructing a group optimization strategy model, performing cold start training based on the basic sample data set, and performing intensive training by using a multi-dimensional composite reward function based on the key sample data set to obtain a dialogue generation model with an emotion cognition-verbal skill expression decoupling architecture; and taking a historical round of dialogue of the to-be-tested system aiming at the current interaction as input of a dialogue generation model, and generating a next round of user reply consistent with the user emotion and the user portrait. According to the invention, deep, efficient and automatic adversarial testing is carried out on the task-oriented dialogue system, so that system defects which are difficult to find by a traditional testing method are effectively exposed.

The invention discloses a software performance test system, method and device in a high-concurrency scene, and relates to the field of software testing, the system comprises a scene intelligent construction module used for generating a concurrency scene through a behavior tree modeling and time sequence prediction algorithm according to service demand parameters and historical traffic data; the distributed test environment scheduling module is used for constructing a distributed test environment by adopting a container arrangement technology; the virtual user load generation module is used for simulating concurrent user requests by adopting a coroutine pool technology; the real-time performance data acquisition module is used for acquiring multi-source performance data of the tested software in real time; the intelligent performance analysis module is used for calculating a core performance index according to the multi-source performance data and carrying out anomaly detection and trend prediction; and the performance bottleneck positioning module is used for mining a dependency relationship among the core performance indexes and generating a bottleneck positioning report and an optimization suggestion document. According to the method, the accuracy, the efficiency and the stability of software performance testing in a high-concurrency scene are improved.

The invention discloses a simulated inquiry interaction analysis method, device and equipment based on man-machine conversation, and relates to the technical field of artificial intelligence and medical treatment, and the method comprises the steps: obtaining inquiry conversation data generated by interaction between a user object and a virtual user; performing multi-dimensional interaction analysis on the inquiry dialogue data based on a preset medical knowledge graph and preset diagnosis information to generate a corresponding evaluation index and a corresponding index score; and generating and outputting an evaluation report containing the index score and the user object-oriented inquiry dialogue improvement suggestion. According to the method, the objectivity and the accuracy of an evaluation result are ensured, prejudice and inconsistency caused by subjective experience difference in manual evaluation are overcome, the evaluation result is accurate, and a user can clearly know the expression level of the user in each dimension and can also obtain a targeted inquiry optimization direction.

The invention relates to the technical field of management systems, and particularly discloses a three-dimensional industrial design material AI intelligent recommendation management system. Comprising a dynamic knowledge graph module, a multi-source perception input module, a neural symbol fusion engine, a situation self-adaptive output module, a self-evolution optimization module, a recommendation rule updating module, a cold start processing module and a multi-target decision module. The neural symbol fusion engine realizes symbol logical reasoning through Transform, the cold start processing module generates a user portrait through gradient embedding and generates virtual user features through cross-map feature propagation, the situation adaptive output module dynamically switches rendering modes according to a design stage, and the self-evolution optimization module performs meta-learning and concept drift detection; through multi-technology fusion and module cooperation, intelligence, precision and high efficiency of three-dimensional industrial design material recommendation are realized, the design efficiency is remarkably improved, and the project landing risk is reduced.

The invention discloses a black box evaluation system for a mobile terminal news recommendation system based on a large model agent. The system is composed of a virtual user layer and a virtual environment layer, the interactive behavior of a specified user group is simulated through a virtual user agent driven by a multi-modal large language model, and continuous interaction with a real news recommendation application online recommendation system is achieved through mobile equipment in the virtual environment layer. The virtual user layer takes a screenshot of a mobile device as input and executes tasks such as content identification and processing, memory storage and retrieval, state response reasoning and interactive behavior decision; the virtual environment layer is responsible for managing a mobile device running a news recommendation application, providing a running state screenshot, and automatically executing corresponding device operation according to an interactive behavior decision of a virtual user; according to the method, the requirements of virtual A / B testing, virtual social experiments and the like of an online recommendation system deployed in a mobile terminal news recommendation application can be met under the black box condition.

The invention discloses a learning progress updating system, method and device and electronic equipment, and relates to the technical field of education, and the system comprises a learning behavior collection module, a behavior change analysis module, a learning progress mapping module and a learning progress adjustment module. The learning behavior acquisition module is used for acquiring learning behavior data of a target student and a first learning progress of at least one virtual user; the behavior change analysis module is used for determining behavior change data of the target student; the learning progress mapping module is used for performing learning progress mapping on the behavior change data to obtain a second learning progress of at least one virtual user; and the learning progress adjustment module is used for generating progress adjustment information corresponding to the at least one virtual user, so that the at least one virtual user is adjusted to a second learning progress. The learning progress of the virtual user is updated based on the behavior change data, the matching degree between the virtual user and the student is improved, and the accompanying learning requirements of the student in different learning stages are met.

The present invention provides a method, device, and system for pushing information resources based on a real-world metaverse, belonging to the field of deep learning technology. The method comprises: collecting a set of real-world user behavior data; obtaining a training data set based on the user behavior data set, and using the training data set to train a deep learning-based neural network to obtain an information resource push model; collecting a set of virtual user behavior data in a real-world metaverse, inputting the virtual user behavior data set into the information resource push model, and outputting metaverse information resource push information. The present invention obtains user behavior data from the real world to train an information resource push model, and then uses data such as user tags collected from the metaverse to utilize the information resource push model trained in the real world to determine information recommendation results that meet the preferences of metaverse users, thereby realizing personalized services for information resources in the metaverse.

The invention relates to an interactive training data generation method and device, vehicle-mounted equipment, a storage medium and a program product. According to the method, historical dialogue data of a vehicle user is obtained, a virtual user model corresponding to the vehicle user is constructed according to the historical dialogue data, and then the virtual user model is utilized to initiate multiple rounds of dialogues to an initial intelligent interaction model. And after each round of conversation, adjusting an emotion label of the virtual user model according to reply information of the initial intelligent interaction model, generating conversation content of the next round based on the adjusted emotion label, and then generating interactive training data according to conversation data and corresponding emotion labels in the multi-round conversation process, the interactive training data is used for training the initial intelligent interactive model. According to the method, massive interactive training data with emotion tags can be generated, and thus the intelligence of an intelligent interaction model trained through the interactive training data can be improved.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit mobility history information associated with the UE. The UE may receive radio resource management information that is based at least in part on the mobility history information, wherein the UE is associated with a virtual UE, and wherein the radio resource management information is a same radio resource management information for each UE of a plurality of UEs associated with the virtual UE. Numerous other aspects are described.

An apparatus including circuitry configured for: wireless charging an energy storage device in the apparatus; using energy from wireless charging and / or the energy storage device to render mediated reality content to a user of the apparatus, wherein the mediated reality content rendered to the user is a virtual scene determined by a virtual point of view within a virtual space, wherein a real point of view of the user, defined by a location and orientation of the user in real space, determines, via a mapping between the virtual space and the real space, the virtual point of view within the virtual space of the virtual user; and in dependence upon a wireless charging parameter, changing the mapping between the real space and the virtual space to enable improvement of the wireless charging parameter.

The application relates to the technical field of the cross of artificial intelligence and behavior science, in particular to a market research system based on multi-source data integration and psychological analysis, which comprises a processing module, an RAG module, a retrieval module, a summary module, an analysis module and a verification module; the processing module processes feedback data of market research; the RAG module retrieves to obtain multi-modal data; the retrieval module retrieves to obtain data samples; the summary module extracts data features; the analysis module analyzes the data samples and generates analysis conclusions; and the verification module verifies the results of the analysis module. The application generates multi-modal data of feedback data in the Internet through the retrieval module, and according to the obtained data samples, the analysis module analyzes to obtain analysis conclusions by combining virtual user models of psychology and / or sociology, so that the problem that the system has weak theoretical support and single data dimension is avoided.

The invention provides a user electricity consumption prediction optimization method and system, a medium and equipment. The user electricity consumption prediction optimization method comprises the following steps: step S11, obtaining original users of an electricity selling company; step S12, screening the original users to obtain a target user; step S13, clustering and grouping the target users to obtain virtual users; step S14, performing dynamic error verification on the user prediction error of the virtual user based on the user prediction error of the target user to obtain an error verification result; step S15, according to the error verification result, repeating the steps S13 to S14 to carry out iterative updating on the virtual user, and obtaining an expected virtual user until an optimal iteration condition is met; and step S16, obtaining the user electricity consumption group of the target user based on the expected virtual user. According to the method, the prediction precision of the electricity consumption of the user can be improved.

This disclosure relates to methods for optimizing virtual user interfaces in a three-dimensional environment. In some embodiments, the computer system changes the level of detail displayed for the corresponding environment. In some embodiments, the computer system applies and adjusts to generate a representation of the physical environment. In some embodiments, the computer system displays user interface objects in a three-dimensional environment with a stereoscopic effect. In some embodiments, the computer system implements light fusion. In some embodiments, the computer system uses visual effects to transition between three-dimensional environments. In some embodiments, the computer system detects movement of the user's viewpoint when displaying a portal to a virtual environment and maintains or stops displaying the portal based on the amount of movement and / or the direction in which the portal is opened. In some embodiments, the computer system outputs different sound effects when initiating the display of different virtual three-dimensional environments.

This application is directed to a method, an apparatus, and a system to, for example, enable a user to interact, manage, and control certain aspects of its own traffic by providing the user with controllable network functions and associated interfaces within the mobile network architecture. In an example method for a user equipment (UE) to control a network service obtained from a network, a control, management, and operation (CMO) function module instantiated in the network may receive from the UE, a request for the UE to control the network service offered by the network. In response to the request, the CMO function module can instantiate at least one network function (NF) configured to be controlled by the UE. The CMO function module can further configure the at least one NF to control the network service in accordance with instructions received from the UE.

The present disclosure provides an information recommendation method, which can be applied to the field of artificial intelligence technology. The information recommendation method includes: obtaining a random access data set generated by randomly accessing different types of information, where the random access data set includes at least one random access data; obtaining first initial recommendation data generated for real users and second initial recommendation data generated for N virtual users, where the N virtual users are fictionalized based on the attribute characteristics of real users, and N is an integer greater than or equal to 1; determining target recommendation data according to the random access data set and the initial recommendation data set, where the initial recommendation data set includes the first initial recommendation data and the second initial recommendation data; and performing information recommendation for real users according to the target recommendation data. The present disclosure also provides an information recommendation device, an electronic device, a storage medium, and a program product.

The present application relates to the technical field of data analysis, and specifically relates to a user portrait label value analysis method and system, comprising obtaining a first subject user portrait label value mapping to form a first user discrete point group, generating virtual user data to be respectively input into a first subject and a second subject clustering model to form a first simulated discrete point group and a second simulated discrete point group, transforming a vector through space fitting records and identifying an unmatched discrete point group, performing cutting and scaling processing on the unmatched discrete point group and recording a cutting and scaling vector, and obtaining a second user discrete point group through coordinate transformation of the first user discrete point group through the transformation vector and the cutting and scaling vector, and obtaining a user portrait label value of the second subject. The present application can realize user portrait conversion across label systems without sharing original user data, and solve the label matching problem caused by loss of normalized information.

Various aspects of the present disclosure relate to a virtual user equipment (VUE) and method for uplink power control by the VUE. The method includes communicatively connecting to and collaborating with at least one second UE to enable a VUE, each UE within the VUE having at least one closed-loop uplink power control loop, with at least a first loop of the at least one loop of each UE assigned to be utilized for VUE communications. The method includes determining, by a processor of the user equipment, a number of trackable closed-loop uplink power control loops for VUE communications as a sum of a number of first loops of each UE within the VUE. The method further includes forwarding to a serving base station of the VUE, an indication of the number of trackable closed-loop uplink power control loops for VUE communications.

A computer system displays, in a first viewing mode, a simulated environment that is oriented relative to a physical environment of the computer system. In response to detecting a first change in attitude, the computer system changes an appearance of a first virtual user interface object so as to maintain a fixed spatial relationship between the first virtual user interface object and the physical environment. The computing system detects a gesture. In response to detecting a second change in attitude, in accordance with a determination that the gesture met mode change criteria, the computer system transitions from displaying the simulated environment in the first viewing mode to displaying the simulated environment in a second viewing mode. Displaying the virtual model in the simulated environment in the second viewing mode includes forgoing changing the appearance of the first virtual user interface object to maintain the fixed spatial relationship.

Some implementations relate to methods, systems, and computer-readable media for digital advertising. In some implementations, a computer-implemented method includes presenting virtual items at a virtual user engagement station. The virtual user engagement station may include a threshold radius for activation of a change in configuration. Upon an avatar crossing the threshold radius, the avatar may be allowed to temporarily wear or interact with the presented virtual items, display different virtual items, and / or purchase virtual items.

The invention discloses a virtual user card strategy generation method and device, equipment and a storage medium, and relates to the technical field of computers. According to the method, a high-personification first card playing strategy is obtained through output of a supervised learning model, a high-competitive-level second card playing strategy is obtained through output of a strategy header of a reinforcement learning model, and the ending probability of a current card game output by the header is predicted according to an end game of the newly added reinforcement learning model. A fusion coefficient is obtained based on the ending probability of the current card game, so that the influence degree of the first card playing strategy and the second card playing strategy on the final card playing strategy is dynamically adjusted; by organically combining the high performance of reinforcement learning and the high anthropomorphic characteristic of supervised learning, not only can the decision-making ability of the game agent in complex games be effectively improved, but also the card playing style of the game agent can be close to that of a real human player, and the game experience of the real player is improved.