511 results about "User participation" patented technology

The invention discloses a hierarchical collaborative management method and system for a virtual power plant based on multi-modal deep learning, and the method comprises the steps: constructing a four-dimensional data collection system, and achieving privacy enhancement preprocessing through federated learning and a differential privacy technology; a Bi-LSTM and a heterogeneous graph neural network are adopted to construct a three-mode deep fusion model, the weight is dynamically adjusted in combination with an environment-user dual-drive attention mechanism, and the load prediction precision and the space resource utilization rate are improved; a multi-target scheduling strategy is generated based on a five-dimensional target function and an improved DDPG algorithm, and physical feasibility is ensured through digital twinborn pre-verification; efficient execution and excitation transparency are realized through edge layer FPGA + NPU hardware acceleration and block chain evidence storage; and constructing a user participation ecology by using a natural language interaction strategy engine and a stepped incentive mechanism. The power grid economy, the equipment reliability and the user participation degree are remarkably improved, and intelligent upgrading of the virtual power plant is promoted.

The invention discloses a non-perpetual culture immersive interactive experience device and system based on a virtual digital human, and relates to the technical field of intangible cultural heritage intelligent interaction, and the device comprises a multi-mode sensing module which collects data such as user actions and voices through a depth camera and the like; the non-perpetual knowledge base module stores a non-perpetual knowledge graph and a case library; the digital human modeling engine fuses the inheritor characteristics and the user data to generate a virtual digital human; the immersion interaction engine constructs a cross-platform rendering environment to realize five-sense fusion experience; and the adaptive learning module analyzes the interaction sequence to optimize the digital human behavior, and all the modules cooperate to realize the intelligent interaction experience of non-genetic culture. Through the multi-modal perception module, the digital human modeling module and the like, the immersive interactive experience of the non-perpetual culture is realized, the user behavior can be accurately captured, the characteristic virtual digital human is generated, the five-sense fusion experience is provided, the content can be optimized based on the user interaction, the inheritance and propagation of the non-perpetual culture are promoted, and the participation degree and the sense of identity of the user are improved.

The invention discloses a charging user behavior pattern analysis system and method, and relates to the technical field of electric vehicle charging management, and the method comprises the steps: obtaining and building a multi-source data pool, fusing the multi-source data pool, analyzing a charging behavior pattern of a user, calculating the abnormal behavior probability, building a dynamic scheduling rule according to the charging behavior pattern of the user, and carrying out the dynamic scheduling according to the abnormal behavior probability. According to the method, through multi-source data collection and analysis, the user charging behavior is accurately predicted, resource distribution is dynamically optimized, the charging station operation efficiency and the user satisfaction degree are improved, virtual power plant integration is promoted, and the power generation efficiency is improved. According to the method, a vehicle-to-power grid strategy optimization module is constructed, the user participation power grid peak regulation potential is quantified, regional energy scheduling is optimized, in addition, an anomaly detection and response mechanism is provided, safety and stability are ensured, and the charging service is promoted to develop towards the efficient, intelligent and sustainable direction.

A social media platform facilitates user interaction through digital environments called “bubbles,” which serve as customizable, collaborative spaces for content sharing and engagement. Users can participate in gamified events such as challenges, races, and raffles within these bubbles. The platform incorporates a blockchain-based reward system that issues digital assets, including tokens and non-fungible tokens (NFTs), based on user participation and performance. Each piece of content shared within a bubble can be assigned its own privacy level, independent of the user's account settings. The system supports role-based access, content moderation, and smart contract integration to ensure secure, transparent reward distribution.

The embodiment of the invention provides a software development method based on artificial intelligence and related equipment. In the embodiment of the invention, an AI software development method and mode are provided, and a user and a technical design document generation agent cooperate to complete a technical design document of a programming task; and the programming agent autonomously performs task planning based on the technical design document, and autonomously executes the programming task based on the planned execution plan. In at least one of the technical design stage or the task execution stage of the programming task, a man-machine cooperation interface is provided, and the man-machine cooperation interface is used for a user to participate in the software development process for the programming task. Therefore, the software development efficiency and the code quality are greatly improved through division cooperation and man-machine cooperation interaction among the intelligent agents.

An online system receives a request to access an interactive geographical map of sources from a client device associated with a user. The system retrieves data describing a geographical location associated with the user. The system identifies one or more sources within a threshold distance of the location and retrieves data including information describing items available at each source. For each source, the system accesses and applies a machine-learning model to predict a user engagement score indicating a likelihood of one or more interactions by the user with a set of items available at the source if the source is included in the map. Based on the score for each source, the system selects a set of sources and generates the map, in which the map indicates the geographical location of each selected source. The map is then sent to the client device, causing the device to display the map.

The invention provides an intelligent optimized arrangement method for a shield construction site. The method comprises the steps that S1, component parameter modeling is conducted on various components of a shield construction site, a knowledge rule base is established, and a component semantic map is established; s2, spatial modeling of a shield construction site and component matching are carried out; s3, on the basis of parameter modeling and rule modeling, constructing a composite target function fusing multiple types of engineering attributes, and outputting a component arrangement scheme meeting a global optimization target, spatial constraint and engineering logic; s4, setting a man-machine collaborative arrangement interface to support a user to participate in adjustment; and S5, based on the component arrangement scheme and the user feedback behavior, calling an arrangement inference engine fusing a historical sample and a feedback learning mechanism, and optimizing the arrangement strategy again. According to the method, the arrangement efficiency and the space utilization rate are improved, the arrangement requirements of complex and irregular sites can be met, multi-target collaborative optimization and conflict automatic detection are achieved, and the method has the arrangement man-machine collaborative adjustment and strategy self-learning capabilities.

Systems and methods for determining user intent and providing targeted advertisements using chat robot interactions are disclosed. The system receives user cues during a chat session with the chat robot and generates a response using a large language model. User intent is extracted by analyzing chat conversations using natural language processing and machine learning techniques. The extracted user intent including weighted keywords and concepts is used to create a user intent profile. Targeted advertising content is generated based on the user intent profile, and the targeted advertising content is provided to the user during subsequent platform interactions. The large language model is continuously retrained using the user participation data to improve intent modeling accuracy. User privacy is maintained by limiting context extraction to chat robot conversations. The system enables personalized and related advertising by inferring user intent via dialog interactions.

The invention discloses an AI-based child story picture book generation method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: generating a narrative framework through employing a BPOT bidirectional pre-training model, carrying out the filling optimization of detailed text paragraphs through combining reinforcement learning and semantic mutual information, extracting dynamic features based on DCNN and SENet, and generating a child story picture book. And an interactive dynamic effect sequence is generated in combination with the preprocessed corpus, and finally, typesetting is optimized through a Wasserstein distance and a variational auto-encoder to generate a child story picture book. By using a BPOT bidirectional pre-training model, reinforcement learning and semantic mutual information to optimize a narrative framework, semantic age suitability and educational target integrating degree are remarkably improved, a DCNN is combined with SENet to generate an age-suitable interaction dynamic effect, interaction trigger point design is fused, immersion and user participation degree of the picture book are improved, and it is ensured that the picture book integrally presents high-quality narrative consistency.

The invention discloses a marketing strategy optimization method based on consumer group behavior analysis, and the method comprises the following steps: deeply integrating and analyzing multi-source heterogeneous data in real time, such as biological characteristic data, physical environment and spatial data, social contact and content interaction deep analysis data, and voice and dialogue analysis data; carrying out association modeling on the behavior data, psychological characteristics, physiological states and social environment factors, and constructing a dynamic holographic user portrait; a large language model and a multi-mode generation model are utilized, marketing content with high personalization and situation adaptation is generated in real time based on a user portrait and a real-time context, and an interactive co-creation mode of the user and AI is explored; and according to an evaluation result, performing online updating and optimization on each link by using a machine learning algorithm to form a continuously improved closed loop. According to the invention, a more accurate and personalized marketing strategy can be provided, the sense of participation of users is enhanced, and the marketing effect and enterprise competitiveness are improved.

The invention relates to the technical field of psychological assessment, in particular to a psychological state assessment method, system and terminal based on an interactive terminal, and the method comprises the steps: separating voice data and text data of a user into an emotion change sequence; based on the emotion tendency of the emotion change sequence, setting an emotion change quantity, and according to a matching relationship between the emotion change quantity and a dialogue situation, calculating a user response duration; obtaining the participation degree of the user at different moments by obtaining the response frequency corresponding to the response duration of the user; combining the degree of participation, the emotional variation and the emotional change probability into an emotional feature, and deducing an emotional classification and a transition label of the current emotional feature; on the basis of the emotion proportion of each emotion classification, dialogue strategy matching is carried out according to the participation amount of the emotion classification at adjacent moments, and a dialogue strategy is set; and the accuracy and effect of emotion recognition are improved.

The invention relates to the technical field of information processing, and discloses a corpus construction method, which comprises the following steps: finely adjusting a large model according to an interaction corpus associated with functions of an intelligent refrigerator to obtain a target large model; inputting the initial corpus into a target large model to generate corpus variants, and screening and / or enhancing the corpus variants to obtain optimized corpus; and performing similarity sorting on the optimized corpora, and screening out target corpora to construct a corpus. According to the method, the large model for generating the corpus is finely adjusted, and the generated corpus is screened and / or enhanced, so that the corpus quality of the corpus is ensured, on the basis, the corpus is automatically generated through the large model, the process that a user participates in constructing the corpus is reduced, the automatic construction efficiency of the corpus is improved, and the user experience is improved. And timely updating of the corpus is ensured, so that the accuracy of the voice interaction function of the refrigerator is improved. The invention further discloses a corpus construction device, a refrigerator and a computer readable storage medium.

The present disclosure provides a search engine optimization (SEO) system comprising a remote server. The remote server comprises a memory with a set of executable routines and a search engine database with multiple fields of applications, each associated with multiple URLs indexed with a user engagement matrix, written data, and a search engine ranking. A processor acquires a web link from a computing device, extracts textual content, analyzes relevancy, and retrieves relevant URLs. The processor evaluates a thematic score, a readability score, and an emotional tone data using NLP techniques, analyzes written data of each URL to determine a topic weight, a legibility weight, and a sentiment tone data, develops a machine learning model, applies the model to recommend content alterations, and renders the alterations at the computing device.

An electronic device for providing a user-participating-type artificial intelligence (AI) training service is proposed. The electronic device may include a user input receiving unit configured to receive, from a user of the service, initial setting user inputs about an initial setting for AI training and to receive an AI training user input for requesting for the AI training. The device may further include a processor configured to provide, through a screen of the electronic device, an initial setting UI (User Interface) receiving the initial setting user inputs and an AI training UI receiving the AI training user input, and a communication unit configured to transmit, to a service providing server, data corresponding to the initial setting user inputs and the AI training user input and to receive, from the service providing server, initial setting data and / or AI training data generated based on the transmitted data.

Techniques are provided herein for providing information during a life cycle of a user's engagement with a product or service. A wireless device is configured to, in response to processing a computer readable artifact after the user has acquired the product or service, transmit a request for first information pertaining to the product or service. A computer is configured to retrieve the first information without regard for the life cycle of the product or service. The computer is further configured to retrieve supplemental information pertaining to the product or service, and provide the first information together with the supplemental information to the wireless device. The supplemental information retrieved varies depending on a current state of the life cycle.

The invention discloses an electric vehicle orderly scheduling method, system and device based on user participation willingness dynamic guidance and a storage medium, and the method comprises the steps: obtaining the initial information of an electric vehicle user and the power grid load information, building a user participation willingness model based on the decision psychology of user participation scheduling and in combination with the initial information, and obtaining a user participation willingness model; the real participation willingness of different types of users in the face of personalized excitation is quantified; and constructing a scheduling model, taking power grid load information and the user participation willingness as model input, setting model constraints according to the initial information, dynamically dividing each EV into resources with different flexibility through a service contract, and matching differentiated constraints and control strategies for the resources. According to the method, the problem that a traditional scheduling strategy neglects the decision-making psychology and participation willingness of the user is solved, a closed loop from user willingness prediction to dynamic regulation of the regulation and control strategy is realized, the user participation degree is guided and utilized, and the stability and economy of a power grid are improved.

A method for identifying a virtual meeting for absent user participation includes identifying, by a calendar application of a first user and based on one or more calendar event criteria, a calendar event that corresponds to a virtual meeting. The first user of the calendar application may be invited to attend the virtual meeting. The method includes causing a calendar application UI to be presented to the first user. The calendar application UI may include a UI element requesting that virtual meeting information be provided to the first user who is unable to attend the virtual meeting. The method includes, in response to a user activation of the UI element, providing a virtual meeting information request of the first user to a virtual meeting application.

The invention discloses a personalized patient nutrition and lifestyle suggestion system based on a large language model. The system comprises a data collection module, a model establishment and optimization module, a result output module and a follow-up visit module, the data quality and reliability are high, and the accuracy and reliability of suggestion generation of the system are improved; an individualized feedback and adjustment mechanism enables the system to better meet personal requirements and preferences of patients; according to the method, cultural and regional differences are considered, personalized suggestions more suitable for specific cultures and regions are generated, improvement of interpretability and understandability helps patients to understand and accept the suggestions generated by the system, a long-term user participation and continuous support mechanism is introduced, and long-term participation and health behavior change of users are promoted.

The invention discloses a building energy scheduling method and platform based on regional energy carbon management, and relates to the technical field of building energy scheduling. The method comprises the steps of multi-dimensional data acquisition, energy-carbon collaborative optimization, dynamic scheduling execution, block chain energy transaction and community-based energy collaboration. The platform comprises a multi-dimensional data acquisition module, an energy-carbon collaborative optimization module, a dynamic scheduling execution module, a block chain energy transaction module and a community collaborative module, and adopts a cloud edge collaborative architecture and a digital twin system. According to the method, double optimization of economy and carbon targets is realized through a cooperation mechanism of a genetic whale algorithm and an NSGA-II algorithm, an energy and carbon credit closed-loop system is constructed by using a block chain, idle energy storage resources are activated in combination with community cooperation, dynamic mapping and early warning are realized by means of digital twinning, and the method is high in practicability. The problems that in the prior art, economy and carbon targets are difficult to balance, energy transaction trust is lost, the user participation degree is low, and carbon management and control lack perspectiveness are solved.

Correlations between a set of linguistic features identified in an unstructured text recited in a source language and a set of user engagement analytic parameters may be measured by a machine learning model selected based on a set of performance metrics from a set of machine learning models trained by a set of supervised machine learning algorithms on (i) a set of unstructured texts recited in the source language and containing the set of linguistic features and (ii) the set of user engagement analytic parameters measured for the set of unstructured texts. The machine learning model grades the unstructured text recited in the source language to determine whether the unstructured text recited in the source language should be (1) edited in the source language and then translated into the target language or (2) translated from the source language to the target language as is.

The invention discloses an English teaching method based on somatosensory interaction, and relates to the field of interactive teaching, and the method comprises the steps: collecting limb behaviors and voice data of a user, and generating a teaching task instruction based on a teaching theme selected by the user; matching actions and voices of a user with a target grammar structure and a vocabulary set by constructing a mapping library of limb behaviors and English communication intentions; analyzing the limb movement data through a space-time diagram convolutional network, recognizing movement features, and generating a voice intention identifier through voice recognition and semantic analysis; comparing the consistency of the limb behavior and the voice intention, and if a conflict exists, generating a correction instruction; and dynamically adjusting the task difficulty according to the historical performance of the user, and increasing visual and voice interference until all teaching objectives are completed. The method has the advantages that by collecting the limb movement and voice data of the user in real time and combining the dynamic task and the intelligent error correction system, the language learning experience with high interactivity is achieved, and the learning effect and the user participation degree are effectively improved.

A dynamic conversation interface system includes a plurality of instances of a large language model (LLM) engine, each instance being configured according to a respective set of system directives. An agent manager engine instantiates and configures the instances of the LLM engine such that a first LLM engine instance is configured according to a first set of system directives, and a second LLM engine instance is configured according to a second set of system directives that is different from the first set. The first LLM engine instance has a different functional specialization from the second LLM engine instance, and the two instances engage in a same conversation session with a user, using the same language dialect, to perform different specializations within that conversation session.

In an interactive media system, for example, in a video game or extended reality (XR) environment, interactive media event information may be received. An interactive media satisfaction value may be determined based on one or more interactive media events received. For example, the event may be scoring a point by the user. When the interactive media satisfaction value is determined to be high, supplemental content with more upbeat themes may be selected for display in the interactive media user interface, while supplemental content with more negative themes, or more comfort-oriented or escapist themes may be selected when the satisfaction value is low. A user engagement metric may also be determined and used for timing, locating, and selecting a mode for presenting the supplemental content.

The invention discloses an incentive differentiation configuration and promotion support system based on user hierarchies, and relates to the technical field of big data and intelligent promotion, and the system comprises a multi-dimensional user data collection module which collects various types of user data and carries out desensitization storage; the user level dynamic evaluation module is used for calculating a comprehensive score through multi-dimensional index weighting and dividing five layers of users; the incentive differentiation configuration module formulates gradient incentive strategies according to different hierarchies; the promotion resource intelligent distribution module distributes promotion resources according to levels, targets and scenes; and the promotion effect tracking feedback module is used for monitoring data, generating a report and dynamically adjusting a strategy to realize optimization. According to the method, accurate division of user levels is realized, the user participation degree is improved through differential excitation, the utilization efficiency is improved through intelligent distribution and promotion of resources, continuous optimization is performed through an effect feedback closed loop, different business targets are adapted, and the marketing promotion accuracy and efficiency are improved.

The invention belongs to the technical field of multimedia publishing management and control, and particularly relates to a distributed multimedia publishing system based on environment interaction control, which comprises an environment multi-dimensional perception fusion module, a dynamic content decision module, a distributed resource scheduling module, a multi-mode interaction feedback module, a publishing quality monitoring module and a supervision center, according to the method, the dynamic environment feature vector is generated by collecting and fusing the multi-source environment data in real time, the content publishing strategy is dynamically generated based on the decision tree algorithm and the user behavior data, real-time linkage of the content and the environment is achieved to reduce manual intervention, and through distributed resource scheduling and intelligent load balancing, the user experience is improved. The resource utilization rate is optimized, energy consumption is reduced, multi-dimensional interaction such as voice, gestures and touch screens is supported to remarkably improve the user participation degree, service continuity is guaranteed by monitoring key indexes in real time and triggering a self-adaptive repairing mechanism, and closed-loop optimization of environment perception, dynamic decision making, resource scheduling and interaction feedback is achieved.

The invention relates to the technical field of data processing, and discloses an electronic book intelligent recommendation method and system based on multi-source data, and the method comprises the steps: collecting user data, score data, a time period, an equipment type and an environment label, and extracting a user feature vector; performing similarity calculation on the behavior characteristics of the to-be-recommended chapter, the score change vector and the user characteristic vector to obtain a first similarity; constructing a current situation vector based on the current position of the user and the real-time weather information, and comparing the current situation vector with the optimal reading situation to obtain a situation matching degree; comparing the historical weather information of the current user with historical weather when the feedback user participates in the scoring behavior to obtain a historical weather matching degree; calculating a second similarity according to the situation matching degree and the historical weather matching degree; and sorting the candidate chapters based on a product of the first similarity and the second similarity to generate a recommendation list. According to the method, personalized recommendation of the electronic book chapters is realized by constructing the user interest map.

A trained model of an online system is used to display elements of a user interface of a user's device in a manner that increases a likelihood of user's engagement. Upon receiving a request from the user for a page of user interface elements and retrieving a set of user interface elements, the online system applies the trained model to predict a likelihood of user's engagement with each user interface element in the set for each incentive amount of multiple incentive amounts. The online system identifies, based on the likelihood of user's engagement with each user interface element for each incentive amount, an optimal incentive amount for each user interface element. The online system ranks the set of user interface elements based on the likelihood of user's engagement for the optimal incentive amount and displays the set of user interface elements at the user interface according to the ranking.

The invention provides a method and device for evaluating live broadcast content quality, a medium and a program product. The method comprises the following steps: in response to a live broadcast content quality evaluation instruction, obtaining a target live broadcast video and attribute related information of the target live broadcast video; obtaining a quality scoring rule matched with the target live video according to the attribute related information; performing feature extraction processing to obtain one or more evaluation feature data corresponding to the plurality of evaluation dimensions; and based on the obtained evaluation feature data, according to the quality scoring rule, performing calculation to obtain scores of a plurality of evaluation dimensions and a comprehensive quality score, so as to evaluate the live broadcast content quality based on the comprehensive quality score. The live broadcast content quality is evaluated through multiple evaluation dimensions, the overall quality condition of live broadcast can be reflected more accurately, the victory or defeat judgment of the live broadcast PK is carried out based on the multi-dimensional comprehensive score, the PK content quality can be guided and improved, and the participation enthusiasm of the user is improved.

The invention relates to an information interaction method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: obtaining query content; displaying query related nodes; the query related node is used for representing a task generated in the process of obtaining the query result of the query content; executing the task represented by the query related node, and displaying an interactive question when the user needs to participate in interaction in the task execution process; the interactive questioning module is used for carrying out at least one of information confirmation and information inquiry aiming at the task; and in response to a reply operation for the interactive question, displaying reply content, the reply content being used for continuing to execute the task to obtain a task execution result. By adopting the method, the accuracy of the content generated by the intelligent agent can be improved.

Example implementations include methods and systems that relate to search results and recommendations in a media content delivery system. An example method includes providing a search query to a multi-task language model associated with a media content delivery system. The method also includes providing user engagement information to the multi-task language model. The user engagement information indicates user engagement activity with the media content delivery system. The method also includes retrieving, using the multi-task language model and based on the search query, one or more candidate media items from a media item database of the media content delivery system. The method also includes identifying, using the multi-task language model and based on the user engagement information, one or more recommended media items from the media item database.