978results about How to "Improve interactive experience" patented technology

The invention discloses an intelligent visualization and text association method for a multi-modal knowledge graph, and relates to the technical field of information processing. According to the intelligent visualization and text association method for the multi-modal knowledge graph, multi-modal data in an internal database of an enterprise is obtained, and a multi-modal feature vector is generated by using a data preprocessing and feature extraction technology; the feature vectors are mapped to a unified vector space through a cross-modal embedding algorithm, semantic alignment, association and fusion among multi-modal data are realized, and a complete multi-modal knowledge graph is constructed. Through bidirectional association and multi-modal joint query, the information acquisition efficiency is improved, and visual display of the knowledge graph is realized by using the graph neural network. Meanwhile, the knowledge graph is dynamically updated through a graph reasoning algorithm, and the timeliness and accuracy of the knowledge graph are ensured. A more efficient solution is provided for an enterprise in the aspects of management and application of multi-modal data, and the intelligent process of knowledge management is promoted.

The invention relates to an aviation standard question and answer optimization method and system based on atlas and document data, and belongs to the field of natural language processing in the aviation field, and the method comprises the steps: S1, recognizing the intention of a user question based on a BERT model; s2, constructing an aviation enterprise standard attribute knowledge graph; s3, constructing an aviation enterprise standard text knowledge base; s4, recalling aviation enterprise standard attribute question knowledge; s5, recalling aviation enterprise standard content question knowledge; and S6, performing big model intelligent question answering based on RAG, and inputting a recall result and an original question of the user into the pre-trained big model through a retrieval enhancement generation technology to serve as knowledge reference to assist in generating answers. According to the method, the knowledge graph of the aviation enterprise standard is constructed, the large model RAG technology based on the knowledge graph is researched, the problem that entities and relations in user questions cannot be intelligently understood in the existing standard attribute information retrieval process is solved, and the accuracy and efficiency of standard attribute information question answering can be improved.

The invention discloses an intelligent building design generation system based on multi-source heterogeneous data and an AI large model, and the system comprises a multi-source heterogeneous data collection and processing module which is responsible for automatically collecting the multi-source heterogeneous data related to a project, and carrying out the data processing; the knowledge graph module is used for carrying out structured storage and association on multi-source heterogeneous data by constructing a knowledge network covering upper planning, historical culture, architectural design standards and law and regulation contents; the AI large model fine tuning module is used for performing fine tuning on the AI large model by using data in the special architectural design field; the scheme design module is responsible for generating various design schemes, providing choices of different design styles and function layouts and optimizing the schemes; and the visual interaction and feedback module is used for providing an interaction interface with a user. The method is remarkably superior to the prior art in the aspects of design substantial content processing, multi-source heterogeneous data integration, design generation and optimization, user interaction experience and the like, and a more comprehensive, intelligent and efficient solution is provided for building design.

The invention discloses an intelligent number-asking large-screen display system and method based on a multi-modal large model, belongs to the technical field of artificial intelligence and big data processing, and aims to solve the technical problem of how to flexibly adapt to diversified application scenes, perform optimization adjustment according to specific scene requirements and improve applicability and pertinence. According to the technical scheme, a multi-mode input processing module is used for receiving input of a user and conducting semantic conversion by means of the natural language processing technology; the multi-modal large model analysis engine module is used for performing analysis and aggregation by means of a trained multi-modal and cross-modal deep learning model; the data processing and integrating module is used for processing and integrating data from different sources in real time according to the output requirements of the analysis engine; and the large-screen visualization display module is used for visually displaying the processed data on a large screen in the forms of charts, thermodynamic diagrams and 3D models by utilizing an advanced data visualization technology and interactive design.

The invention discloses a method for correcting dialogue intention information of old people based on a deep neural network, and particularly relates to the technical field of dialogue optimization, and the method comprises the steps: collecting and cleaning multi-topic multi-round dialogue data, marking multi-round dialogue corpora, and unifying the format; performing feature extraction on the labeled corpus by using the multi-intention recognition sub-model to generate a multi-intention representation vector capable of representing each intention; screening context content related to the target intention in combination with a hierarchical attention mechanism of user context dynamic weight adjustment; processing context content related to the target intention through gating operation based on multiple rounds of interaction history, and reserving semantic fragments with reference value; performing parallel analysis on the reference semantic fragments based on a multi-task learning structure of a deep neural network, performing classification processing on different intentions, and calculating scores; and executing multi-intention fusion correction operation according to classification and scoring results, and outputting intention information capable of distinguishing each intention.

Along with promotion of industry 4.0 and rising of intelligent manufacturing, an industrial decision support system plays a more and more important role in improving enterprise operation efficiency and market competitiveness. The invention provides an industrial decision support system based on big data and artificial intelligence technology, and aims to provide accurate decision support for enterprises through deep analysis and real-time processing of massive industrial data. According to the system, by integrating an advanced data acquisition technology, monitoring and data capturing of the whole process of industrial production, including but not limited to production equipment states, process parameters, quality control, supply chain information and the like, are realized. By using artificial intelligence algorithms such as machine learning and deep learning, the system can identify a mode and predict a trend from complex data and construct a corresponding decision model. In addition, a built-in operation optimization engine of the system can provide an optimal solution for production planning, inventory management and resource configuration based on a data analysis result. Through an intuitive user interaction interface, a decision maker can easily obtain key business insights and intelligent decision suggestions so as to make a quick response in a continuously changing market environment. The industrial decision support system not only can improve the production efficiency and the product quality, but also can help an enterprise to reduce the operation cost, avoid potential risks, and promote the enterprise to transform to intelligence and digitization.

The invention discloses an intelligent customer service method for adaptively adjusting an interaction strategy by using reinforcement learning, and the method comprises the following steps: S1, obtaining a natural language text inputted by a user, and generating a multi-dimensional state vector; s2, grouping the users by using a real-time dynamic clustering algorithm, and updating a clustering result; s3, generating an action space in a specific state, and enriching the action space in combination with a rule-based strategy and a learning-based strategy; s4, aggregating neighbor node features through a graph convolutional network, and extracting local features; s5, weighting adjacent node features by using a graph attention network, and dynamically allocating attention weights; s6, carrying out interaction strategy optimization by adopting a spiral ladder type deep exploration network, and optimizing action selection; and S7, combining online learning with an experience playback mechanism, continuously updating an interaction strategy, and making a quick response to dynamically changing user demands. According to the method, reinforcement learning, the graph neural network and the sentiment analysis technology are combined, and intelligent customer service interaction strategy self-adaptive adjustment and optimization are achieved.

The invention discloses a mechanical arm operation method based on a multi-mode large visual language model, which comprises the following steps of: firstly, acquiring image data of a mechanical arm operation scene through a visual sensor, and acquiring a user instruction in combination with a voice recognition module or a text input module; and inputting the natural language instruction and the visual scene data into a multi-modal large visual language model for multi-modal task analysis. The model identifies the category, position and attribute of a target object in a scene, and generates a specific operation sequence in combination with an input instruction. And then, according to the operation sequence generated through analysis, the system directly drives the mechanical arm to execute corresponding tasks including specific actions such as grabbing, moving and placing of the target object, and in the task execution process, the mechanical arm sequentially completes the actions according to the operation sequence generated in advance. The problems that in the prior art, a mechanical arm is inaccurate in complex task instruction analysis, poor in operation flexibility and adaptability and poor in real-time response capacity in a dynamic environment are effectively solved.

The invention relates to the technical field of artificial intelligence, and discloses a man-machine dialogue history and semantic retrieval-based prompt automatic construction method, which comprises the following steps of S1, performing text preprocessing on historical dialogue data and user input, including dynamically generating query keywords, verifying and analyzing a file uploaded by a user, and extracting core contents; s2, utilizing a pre-training language model to map the historical dialogue and the user request into semantic vectors, matching in combination with the keyword weight, and constructing a historical vector set and a user request vector; and S3, extracting a context fragment most relevant to the user request from the historical dialogue vector based on a convex optimization method. The context information highly related to the user request is accurately extracted through the sparse optimization technology, and the background information, the user request and the generation instruction are organically integrated in combination with the dynamic Prompt template design, so that the semantic correlation and context coherence of the generated reply are improved, and the interference of redundancy and irrelevant information is avoided.

The invention provides an image rendering method and device, electronic equipment and a storage medium, and the method comprises the steps: calculating a distance between a virtual image obtaining device and a to-be-rendered object through determining the to-be-rendered object in a to-be-rendered scene, and determining the distance as a first loading factor; determining a rendering picture pixel proportion of each to-be-rendered object based on preset view cone size information, determining the rendering picture pixel proportion as a second loading factor, generating a rendering loading priority sequence according to the first loading factor, and determining a model level resource file and a texture level resource file according to the second loading factor, loading the resources to a video memory for rendering according to the sequence; the priority is determined by calculating the distance between the camera and the to-be-rendered object, it is ensured that a high-quality model and texture of a close-range object are loaded preferentially, the instantaneity of the rendering loading process is improved, texture and model grade division is conducted through the pixel proportion of the to-be-rendered object in the picture, and the rendering efficiency is improved. The occupation of a video memory is reduced, and the overall rendering performance of the system is improved.

The invention discloses a live broadcast method and device for free matching combined e-commerce operation, and the method comprises the steps: S1, collecting and analyzing user data, and building a user portrait; s2, based on the user portrait and the real-time behavior data, generating and dynamically updating a personalized commodity recommendation list; s3, in the live broadcast process, the anchor displays a commodity combination effect and provides a real-time interaction function; s4, virtual reality and augmented reality technologies are adopted to realize virtual commodity display and trial; s5, analyzing the real-time behavior data of the user by using an improved collaborative filtering algorithm, and recommending related commodities; s6, analyzing the emotional tendency of the user in interaction by adopting a multi-modal fusion emotion analysis algorithm, and providing personalized interaction suggestions for the anchor; and S7, providing an integrated online shopping function, and supporting the user to seamlessly complete the purchase operation. Through the technical steps, the personalized shopping experience of the user is improved, the live broadcast interactivity is enhanced, and the method has the beneficial effects of high recommendation accuracy, strong participation sense of the user and the like.

The invention relates to a light control method and system based on a holographic interactive projection technology, and the method comprises the steps: projection region recognition, user interaction detection, light parameter calculation and light real-time regulation and control, the projection region recognition, scanning of a target region through a holographic projection device and a depth induction sensor, and generation of a three-dimensional space model of an environment; a motion capture device and a deep learning algorithm are used for carrying out real-time recognition on gestures or motions of a user, interaction intentions and priority ranking are generated, a holographic projection device is used for generating a three-dimensional environment model, the motion capture device recognizes the intentions of the user, and an illumination optimization model is used for calculating regulation and control parameters; and the output of the light equipment is dynamically adjusted, so that high-precision and intelligent light control is realized, and the problems that a traditional light control method is insufficient in environment perception capability, lacks a user interaction mode, is limited in flexibility and adaptability of light regulation and control, and lacks a multi-module cooperative working mechanism are solved.

The invention discloses a touch control method based on a pressure sensor, which relates to the technical field of sensor equipment, and comprises the following steps: designing a touch control panel; distributing and calibrating a sensitivity area; designing a multi-layer touch pressure sensing fusion algorithm; designing a dynamic pressure feedback mechanism; designing a nonlinear pressure interval classification mechanism; and performing pressure sensing and dynamic gesture recognition. According to the touch control method based on the pressure sensor, through multi-level design and innovative model optimization, innovative technologies such as differential sensitivity design, a dynamic sensitivity adjusting mechanism, pressure sensing and gesture recognition are introduced into the touch control technology of the pressure sensor, so that the precision and efficiency of complex gesture analysis can be remarkably improved; and the false touch rate is effectively reduced. The design can adapt to various environment changes, the service life of equipment is prolonged, the user interaction experience is improved, and the defects in the prior art are overcome.

The invention discloses an implementation method for intelligent agent data analysis based on a large language model, and the method specifically comprises the following steps: S1, constructing an intelligent agent model which comprises a business index system module, a task planning module and an execution module; s2, a user inputs a real-time query demand to the constructed agent model, and the agent model performs semantic analysis on the input query demand based on a large language model to obtain a query target; s3, inputting the obtained query target into a task planning module, and performing task planning by the task planning module according to the query target and generating a task query result; s4, the execution module visualizes the generated task query result and displays the visualized query result on a display screen, and data analysis and display are completed. According to the method, semantic analysis is carried out on the natural language text by means of the large model agent, the real-time query requirement of the user is quickly and accurately understood, and the interaction experience is improved.

The invention discloses a chronic disease follow-up visit and management platform driven by a large model, and relates to the technical field of medical information technology platforms. The system is applied to managing and tracking the follow-up visit process of chronic disease patients and providing health consultation and answers, and comprises a user interface module, a logic control module, a database module, a large model module and an auxiliary function module, and the user interface module is used for providing an interactive interface between a patient and a doctor. An intelligent and efficient system platform is constructed by integrating a large model technology, a voice recognition technology and a digital human technology, the system platform adopts a privatized large model, data security and privacy protection are ensured, medical institutions are allowed to autonomously optimize and control the application of the model, and on the whole, through an advanced technical means, the intelligent and efficient system platform has the advantages of being high in practicability and easy to popularize. Refining, individuation and high efficiency of chronic disease management are remarkably improved, and the purpose is to improve the health outcome and life quality of patients.

The invention provides a medical AI question and answer method based on retrieval enhancement, which comprises the following steps: acquiring a medical professional knowledge base, and constructing an entity recognition model and a medical knowledge graph; the method comprises the following steps: splitting a medical professional knowledge base, and creating a vector index and a full-text retrieval reverse index; intention classification is carried out, and initial processing is completed; performing multi-path mixed retrieval on the medical professional knowledge base to obtain a user question related text block; a filtering rule is preset, and the user question related text blocks are filtered; answering the user question according to a preset second prompt word, and answering the user question according to a preset third prompt word when the user question exceeds the range of the medical professional knowledge base or the multi-path mixed retrieval has no result. According to the method, related context information can be accurately searched, reliable reference information is provided for a generative large model to answer professional questions, the interactive experience of a medical question answering system is improved, and the accuracy and specialty of answer generation of the system are remarkably improved.

The invention discloses a network topology and equipment resource information display method and device, equipment, a medium and a product, and relates to the field of network topology monitoring, and the method comprises the steps: employing a data collection module to collect network data; the network data comprises network topology information and resource information; carrying out optimization processing on the network data by utilizing a data processing module, and determining optimized network data; dynamically generating a network topology view according to the optimized network data by using a generation module of a display screen interface on the basis of the equipment operation state and the site connection relationship; based on a user interaction module, the link information of each link, the basic information of each network node and the resource state information in the network topology are displayed in a graded mode according to the network topology view, the information display effect in a large-scale network environment is optimized, and the resource state can be displayed in real time.

The invention discloses an intelligent interactive Agent system based on Langchain and an implementation method, and relates to the technical field of natural language processing and artificial intelligence. Comprising the steps of 1, establishing an intelligent interactive Agent system by using an interface and an integrated tool provided by a Langchain framework, 2, managing calling of various tool modules and services through a central scheduling module, and dynamically registering and unbinding the tool modules by using the interface provided by the Langchain framework, and 3, processing user input by using a large language model through a process management module, and establishing an intelligent interactive Agent system. 4, a series of tool modules are integrated through the integrated tool management module, the tool modules comprise a text search tool, a weather query tool and a video information acquisition tool, each tool module works independently or is in linkage with other tool modules, and the tool modules are connected with the integrated tool management module. And 5, managing a user interaction interface through a front-end management module, supporting a user to query and control in a natural language, displaying a processing progress and a processing result in real time, and providing feedback and help information.

The invention relates to a vehicle-mounted user intention recognition and task generation system based on a large model, and relates to the technical field of automobile interaction. The user intention analysis module is used for obtaining voice input of a user in a vehicle and analyzing the voice input to obtain a plurality of user intentions; the situation awareness module is used for collecting current environment data of the vehicle and obtaining a current situation based on the current environment data through a large model; the task generation module is used for searching a task capability interface of a vehicle according to the user intention and the current situation to generate a task combination; the task combination is to call different agents; the reflection module is used for evaluating whether the generated task combination is consistent with the user intention and the current situation and adjusting the inconsistent task combination; and the task sequence arrangement module is used for confirming the control sequence of different series-parallel tasks according to the task combination and calling the corresponding agents.

The invention discloses an enterprise micro-marketing auxiliary method and system based on a large language model. The efficiency and effect of marketing are improved by using the large language model. According to the method, by integrating a vector database, an embedded model and a context learning technology, the capabilities of real-time understanding of user intentions, personalized reply and quick service change adaptation are realized. The method has the core advantages of accurate user demand analysis, personalized service provision and efficient knowledge retrieval system. By analyzing user behaviors and dialogue records, product recommendation and marketing strategies according with user preferences can be provided. In addition, the method also has a real-time verbal skill updating capability, so that the timeliness and accuracy of information are ensured; the automatic order information extraction technology improves the information processing efficiency, and reduces the time and cost of manual operation. According to the invention, the marketing efficiency is improved, the interactive experience between the user and the customer service is enhanced, and competitive advantages are provided for enterprises in the market with intense competition.

The invention discloses a vehicle-mounted intelligent scene generation method and device based on a large model, equipment and a storage medium. The method comprises the following steps: receiving user expression information input by a user, and outputting user intention information according to the user expression information by utilizing a preset large language model; a new vehicle scene card is determined to be generated according to the user intention information, or a target vehicle scene card matched with the user intention information is determined by using a knowledge graph, and the knowledge graph comprises historical vehicle scene cards; and controlling the current vehicle according to the execution action in the new vehicle scene card or the target vehicle scene card. According to the technical scheme of the embodiment of the invention, the new scene card is generated or the matched historical scene card is found, so that the problem that the scene card lacks flexibility and individuation is solved.

The invention provides a digital human control method and device based on multiple modes and electronic equipment, and relates to the technical field of data processing. In the method, voice data, facial expression data and body movement data of a user are acquired, and the user interacts with a digital human; performing semantic analysis on the voice data by adopting a Transform model to obtain an emotional state and a language habit corresponding to the user; performing feature extraction on the facial expression data by adopting a convolutional neural network model to obtain a facial expression type corresponding to the user; performing action analysis on the limb action data by adopting a hidden Markov model to obtain effective action features corresponding to the user; generating a fusion result based on the emotional state, the language habit, the facial expression type and the effective action features; and adjusting the multi-modal output corresponding to the digital human according to the fusion result. By implementing the technical scheme provided by the invention, the interaction experience feeling of the user can be improved.

The invention provides a virtual digital population type synchronization method, system and device, a medium and a program product, and the method comprises the following steps: analyzing an input voice signal, and obtaining a voice feature; taking the voice features as input of a lip movement prediction model, and predicting corresponding lip movement parameters; driving a face model of the virtual digital human to perform real-time rendering according to the lip movement parameters, and realizing fine movement control of lips; and obtaining user feedback data, and continuously optimizing and adjusting the lip movement prediction model based on the user feedback data. Through advanced technologies such as deep learning, voice analysis and lip movement prediction, accurate synchronization of the virtual digital population type and the voice content is realized, and the expression ability of the virtual character and the user interaction experience are improved.

The invention provides an interaction method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: carrying out the semantic analysis of a to-be-processed problem, and generating a reply text and a target action of the to-be-processed problem; determining a first text matched with the target action from the reply text according to the reply text and the target action; performing time alignment on the execution starting time of the target action and the playing starting time of the first text; the reply text is played, and in the playing process of the reply text, according to the execution starting time of the target action and the playing starting time of the first text after time alignment, the target action is synchronously executed when the first text is played, so that synchronization of the action and the reply text can be realized; and the interaction performance is improved.

The invention discloses a user question answering method and device, equipment and a medium, and relates to the field of artificial intelligence, and the method comprises the steps: obtaining the input information of a user; performing application scene analysis on the input information and semantic intention understanding on the input information by using a multi-level associated scene analysis model, and determining an actual application scene of the input information; calling a core element template preset for the actual business scene, and extracting core element information in the input information according to the core element template; and acquiring scene data, inputting the reference knowledge, the cue word and the scene data into the trained large language model as input data, and obtaining a reasoning result output by the large language model. According to the method, the data correlation problem that knowledge quoted by an existing LLM is inaccurate and incomplete is solved, association matching between the problem and business scene data is perfected, and therefore the reply effect of the LLM on scene related problems of all industries and fields is improved.

The invention relates to the field of modern man-machine interaction, in particular to an LUI and GUI method and system based on an emotion module. According to the technical scheme, the LUI and GUI method and system based on the emotion module comprise a dynamic GUI generation and adaptation module; compared with a traditional GUI system which generally depends on a preset interface design and a fixed interaction mode when interacting with a user and lacks active perception and active response ability to the emotion of the user, due to the defect, the user experience is not personalized enough, dynamic adjustment cannot be carried out according to the instant emotion state of the user, and the user experience is poor. According to the LUI and GUI system based on the emotion module, the language user interface is introduced to interact with the user, so that the defects in the prior art are overcome, the LUI can have a dialogue with the user through a natural language processing technology, and the system can call a dialogue management function by analyzing the emotion of the user, so that a response and interaction page conforming to the current emotion of the user is generated.

The invention provides an intelligent data analysis and knowledge question and answer method and system based on a multi-modal large model. The method comprises the following steps: receiving a multi-modal query request, performing semantic analysis and intention recognition technologies, determining a question core and a required knowledge field, and generating a personalized question understanding framework; performing manifold embedding processing by applying a manifold learning enhancement algorithm, revealing an internal geometric structure, constructing a shared representation space by adopting a multi-task learning technology, training a plurality of sub-tasks at the same time, and generating cross-modal unified representation; performing recurrent processing by using a recurrent neural network algorithm, recursively updating an internal state, constructing an organized information structure by using a hierarchical clustering method, and generating an ordered information structure chart; a context awareness feedback mechanism is introduced, instant response and environment change are monitored in real time, an answer strategy is dynamically adjusted, instant feedback is recorded, and an intelligent data analysis and knowledge question and answer scheme is generated. According to the technical scheme provided by the invention, the accuracy of intelligent data analysis and knowledge questions and answers and the user experience are improved.

The invention discloses a meta universe-based conference interaction method, and relates to the technical field of virtual conferences, and the method comprises the steps: extracting the facial features of participants, comparing the facial features with a pre-established facial feature library, obtaining the unique identity of each participant, and recognizing the identities of the participants; after the identities of the participants are determined, position changes of key body joint points of the participants are detected in real time, and specific actions of the participants are judged by analyzing relative positions and movement tracks between the joint points; the method comprises the following steps: receiving the acoustic characteristics of the participant language, converting the voice signal of the participant into a text, and analyzing the semantics and emotion of the text in combination with natural language processing to obtain the language expression intention of the participant. According to the method and the device, the optimal interaction mode can be dynamically selected from the preset library according to different interaction intentions, and the audio and video parameters and the interface layout are adjusted in real time, so that intelligent interaction in a multi-user scene is realized, the interaction experience of a conference is optimized, and the interaction effect can also be improved.

The embodiment of the invention discloses a page display method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps that a target video is played in a preset page, an object identifier set associated with the target video is displayed in the preset page, and the object identifier set comprises object identifiers corresponding to a plurality of explanation objects associated with the target video; the object identifier set comprises a first object identifier displayed in a first display mode and a second object identifier displayed in a second display mode, the first object identifier is used for triggering a preset interaction event of a corresponding explanation object, and the first object identifier comprises an object identifier corresponding to a first target explanation object; the display state of the first target explanation object meets a preset condition. By adopting the technical scheme, automatic change of the object identifier display mode can be realized according to the display state of the explanation object, and the viewing experience and the interaction experience can be improved.

According to the voice robot interaction method and device based on the integrated ASR, the medium, the program product and the terminal provided by the invention, rapid deployment and optimization of an intelligent voice interaction system are realized by integrating a mature third-party voice recognition technology and a self-developed voice event model; product deployment and use can be quickly completed when the system enters a new region and a language market, the recognition capability is greatly enhanced, the user interaction experience is optimized, low-delay and smooth and natural interaction is realized, and the adaptability and competitiveness of the product are improved.