172 results about "Content adaptation" patented technology

The invention discloses a collaborative personalized learning system and method based on a large model, and relates to the technical field of collaborative learning, and the system collects and fuses multi-modal data, generates a student state vector, plans a personalized learning path based on the state and a knowledge graph, and generates multi-modal explanation content according with the student style. The method comprises the following steps: extracting a student reasoning path, identifying thinking deviation, analyzing task performance, generating a path and content adjustment suggestion, identifying a motivation state, triggering an intervention strategy, receiving a teacher strategy, and realizing path and style co-construction. The multi-modal content of the matched style is generated, adaptive intervention is achieved in combination with inference analysis and emotion adjustment, and the learning efficiency and the teaching response intelligent level are improved.

The invention relates to the technical field of marketing strategies, in particular to an intelligent marketing service platform and method for financial services, and the platform comprises a user behavior analysis module, a customer classification module, a content adjustment module, a marketing strategy optimization module and a market trend prediction module. According to the method, the behaviors and preferences of the users can be accurately predicted by monitoring the behaviors of the users and identifying key interaction events of the users, customer groups can be more finely divided by classifying the customer data, more customized services are provided for different customer groups, the personalized experience of the customers is enhanced, and the user experience is improved. The marketing strategy is adjusted in real time to respond to the change of the market and consumer behaviors, so that the enterprise can keep leading in the market with intense competition, and the perspectiveness of the marketing strategy is enhanced through the dynamic prediction of the market trend, so that the enterprise can predict and adapt to the market change and keep the competitive advantage.

The invention discloses an intelligent bid invitation file generation method and system based on text automation, and relates to the technical field of artificial intelligence and data processing, and the method comprises the steps: carrying out the semantic analysis of a bid invitation demand text through a project type recognition model, and extracting a feature vector and a keyword set of a project; based on the feature vector, a cosine similarity algorithm is adopted to retrieve a matching template in a preset bid invitation file template library, a candidate template list is generated, and label classification and parameterization setting are carried out on templates of the candidate template list; based on the keyword set, carrying out content adaptation on templates of the candidate template list, and generating an initial bid invitation file; and performing segmented auditing on the initial bid invitation file, adjusting the keyword set in combination with auditing opinions, and synchronously updating the keyword set to the parameterized database through the mapping relationship to generate the bid invitation file. According to the invention, closed loop from demand to achievement is realized, labor cost of bid invitation file compiling is reduced, and bid invitation file quality and generation efficiency are improved.

The invention relates to the technical field of AI dialogue generation, and discloses a child AI dialogue generation method and system based on IP role personalization, and a storage medium. The method comprises the following steps: acquiring IP role personal setting data and constructing a character feature sub-vector, a style feature sub-vector and a knowledge feature sub-vector; performing man-set weight attention calculation on the text input by the user to obtain an attention weight distribution matrix; joint optimization is carried out through a multi-target man-set constraint loss function, and intermediate dialogue content meeting an IP role man-set constraint condition is obtained; and carrying out education content adaptation and role identity consistency verification based on the intermediate dialogue content to obtain a pre-generated dialogue text, and carrying out real-time man-set deviation correction to obtain a target dialogue generation result. The method can continuously monitor and correct the human setting deviation phenomenon in the dialogue generation process, ensures that the generated content always conforms to the IP role setting, and effectively solves the technical problem of role identity drift in multiple rounds of dialogues.

The invention discloses a recommendation data enhancement method based on a fine-tuning large language model, and the method comprises the following steps: S1, determining an optimization target of a data enhancement task and designing a corresponding instruction template for a core task in combination with user-article interaction characteristics and auxiliary information in a recommendation system scene; s2, adjusting parameters of the large language model according to related contents of the data enhancement task by adopting a lightweight fine tuning technology to generate data highly aligned with the core task so as to finely tune the large language model; s3, generating new user-article interaction data by fine tuning the large language model, and supplementing article feature information and enhanced data of a project summary; and S4, integrating the enhanced data with the original data of the recommendation model to optimize the training of the recommendation model. According to the method, user-project interaction is enhanced, project attributes are enriched, a high-quality project summary is generated, the problem of data sparsity is effectively relieved, and the generalization ability and recommendation effect of a recommendation system are improved.

Systems and methods are presented herein for requesting a version of media content from a server that includes haptic feedback rending criteria compatible with the haptics capabilities of a client device. At a server, a request is received for a media asset for interaction on a haptic enabled client device, wherein the media asset comprises haptic feedback rendering criteria. Based on the request, haptic feedback capabilities of the haptic enabled client device associated with the request is determined. The haptic feedback capabilities of the haptic enabled client device are compared to the haptic feedback rendering criteria of one or more versions of the media asset available via the server. In response to the comparing, a version of the media asset comprising haptic feedback rendering criteria compatible with the haptic feedback capabilities of the haptic enabled client device is transmitted from the server to the haptic enabled client device.

The invention relates to the cross technical field of artificial intelligence and multimedia communication, and discloses an intelligent optimization system and method fusing video resource scheduling and voice emotion recognition, and the system comprises a voice emotion recognition module which is used for collecting a user voice stream in real time, extracting acoustic features through a deep learning model, carrying out the emotion classification, and obtaining a voice emotion recognition result; and outputting the emotion label. According to the invention, through voice emotion recognition, the system realizes personalized resource allocation and content adjustment, so that the personalization and intelligence of user experience are greatly improved; the video resource scheduling module dynamically adjusts parameters according to a network, equipment and emotions to ensure smooth playing of a video and excellent image quality and tone quality; a multi-modal decision engine fuses a multivariate data generation strategy, resource utilization is optimized, and the emotion matching degree and the QoS score are improved; the intelligent optimization method is clear in process, video resources are accurately optimized, strategies are continuously updated through user feedback, the system adaptability is enhanced, and high-quality and personalized multimedia service experience is comprehensively provided for users.

To more easily implement synchronization of reproduction timing of a content in a plurality of user terminals.SOLUTION: A processing device comprises: a content acquisition section which acquires a content to be distributed to a plurality of user terminals from a server; a content transmission section for transmitting the content to a first user terminal, which is a user terminal including the processing device in a distribution path of the content from the server, in the plurality of user terminals; an adjustment time acquisition section for acquiring an adjustment time of distribution of the content to the first user terminal, the adjustment time being calculated on the basis of a reference time set to a first group to which the first user terminal belongs; and a delay control section which delays the transmission of the content to the first user terminal by the content transmission section so as to synchronize the distributions of the content to the first user terminal and one or more user terminals belonging to the first group, on the basis of the adjustment time.SELECTED DRAWING: Figure 1

The invention discloses a teaching simulation system based on VR glasses, particularly relates to the technical field of education, and comprises a data acquisition module, a data processing and analysis module, a teaching content adjustment module, a feedback generation module and a learning terminal. The teaching simulation system based on the VR glasses comprises a data acquisition module, a processing analysis module, a teaching content adjustment module, a feedback generation module, a learning terminal module and the like. The data acquisition module acquires multi-aspect data of students through various sensors and a VR auxiliary acquisition module; the data processing and analysis server processes the data by using technologies such as deep learning and calculates the attention index and emotion intensity of the student so as to determine subsequent operation; the teaching content adjusting module dynamically adjusts the teaching difficulty and mode according to the analysis result; the feedback generation module provides emotional feedback; the learning terminal comprises VR glasses and related equipment for assisting teaching. According to the system, various advanced technologies are integrated, and a highly personalized, immersive, intelligent and adaptive teaching environment is created for students.

The invention discloses a dynamic adaptation method and device for display content of an LED screen and a medium, and the method comprises the steps: collecting original feature data of audiences in a radiation range of the LED screen through a multi-mode biosensor, carrying out the preprocessing of the original feature data, and generating a desensitization feature vector through local anonymization processing; performing real-time analysis on the desensitization feature vector by using a multi-modal fusion model in an edge computing node to generate a primary emotion tag; uploading the primary emotion label and the associated historical behavior data of the audience to a cloud platform so as to predict potential interests of the audience through a preset emotion deep analysis model, and generating a dynamic content adaptation strategy in combination with the potential interests of the audience; on the basis of a dynamic content adaptation strategy, display content matched with the emotion label is called from a pre-stored material library, low-delay rendering is conducted on the display content, and color parameters and the content display sequence of the LED display screen are dynamically adjusted according to the emotion analysis result.

The invention discloses a live broadcast content adjustment method and system based on user interaction behavior analysis, and belongs to the field of image communication, the live broadcast content adjustment method based on user interaction behavior analysis comprises the following steps: processing real-time bullet screens, filtering invalid information by using an NLP technology, obtaining a first processing bullet screen, and combining a domain knowledge base to obtain a second processing bullet screen; performing standardized expression on the first processing bullet screen to obtain a second processing bullet screen, extracting key demand words in the second processing bullet screen, and obtaining a third processing bullet screen; an improved BIRCH clustering algorithm is adopted, bullet screen merging requirements are processed from the third step based on semantic similarity, and the clustering cluster popularity is calculated in real time according to the formula that popularity = occurrence frequency * speaking user value weight; the method has the beneficial effects that the barrage content in the live broadcast process is processed, and the current user requirements are ranked, so that an anchor can intuitively obtain common requirements of most audiences, voting is not needed to be initiated to aggregate user opinions, and the efficiency is high.

The invention discloses an intelligent communication content adaptation system and method based on user intention recognition. The system integrates and processes texts, voices, emoticons and unstructured behavior data through a multi-modal input analysis module; the deep learning intention recognition engine adopts a triple attention mechanism, current input and weighted historical interaction features are fused, and multi-level intention classification including basic operation, semantic targets and emotion driving is output; the real-time emotion state analysis module fuses acoustics, semantics and physiological indexes to generate a dynamic emotion matrix; the content adaptation decision engine is based on the intention confidence and the emotional state; and the multi-channel output optimization module performs cooperative adjustment on the speech synthesis rhythm, the text abstract and the visual interface according to the speech synthesis rhythm and the text abstract. According to the method, the perception precision of the deep intention and emotion of the user in a complex scene is remarkably improved, the individuation and multi-channel adaptive optimization of the response content are realized, and the communication efficiency and the user experience are effectively improved.

The invention relates to the technical field of auxiliary writing systems, in particular to a structured auxiliary writing system based on multi-agent collaboration. The system specifically comprises a writing task demand analysis and modeling module, a multi-agent system architecture construction module, a writing task disassembly and subtask distribution module, a multi-source knowledge retrieval and integration module, a structured content generation module, a format specification and quality evaluation module, a logic verification and content adjustment module and a user feedback iteration and model optimization module. The writing task demand analysis and modeling module firstly performs surface analysis on a writing task of a user, determines the type, theme, target audience, core demand and quality requirement of the writing task, and converts a fuzzy writing demand into a quantifiable and executable structured task model; according to the invention, the limitation of a traditional writing mode and an existing single-function auxiliary tool is solved.

The invention belongs to the field of artificial intelligence and personalized audio recommendation, and discloses an intelligent radio content dynamic adjustment method based on scene perception. The method comprises the following steps: extracting an original feature vector according to multi-dimensional information of a user, and preprocessing the original feature vector to obtain a standardized user state input vector; determining a current scene label of the user according to the standardized user state input vector and a scene recognition model; according to the current scene label, screening adaptive audio content from a content library of the intelligent radio station, and constructing a candidate content structure set; generating a user portrait vector according to the historical behavior data; according to the user portrait vector, reordering each piece of candidate content in a candidate content structure set to obtain a recommended content sequence; and pushing to the user according to the recommended content sequence, and updating a user portrait vector based on behavior feedback. According to the method, the user experience and the content adaptation accuracy are remarkably improved, and a complete closed-loop feedback learning mechanism is constructed.

Provided is a system and method for dynamically adjusting a descriptive document with instructions for a user interface based on configuration settings and software version and / or release for a particular user and document data stored in a technical data object. The process ensures that the content of the descriptive document matches what a user will see on a screen when viewing the user interface. In one example, the method may include retrieving user interface configuration settings generating a simulated user interface that includes a plurality of user interface elements and formatting the user interface elements based on the user interface configuration settings, composing a window with text from a document and screenshot images of one or more formatted user interface elements from the simulated user interface corresponding to the text, and rendering the window via a display of a computing device.

The invention belongs to the technical field of culture propaganda and display, and particularly relates to an immersive culture propaganda system based on an AR technology. Comprising a characteristic culture resource library module, a user portrait analysis module, a culture deep hierarchical analysis module, an immersive narrative engine module, an autonomous exploration interaction module, a dynamic content generation module, a multi-sensory experience enhancement module and a feedback optimization module. Each module takes a characteristic culture resource library as a content basis, takes a user portrait analysis module as a demand guide, realizes content adaptation through a culture deep layering analysis module, and creates an interesting and autonomous experience form by means of an immersive narrative engine, autonomous exploration interaction and multi-sensory experience enhancement module. The content freshness feeling is kept by means of the dynamic content generation module, finally, full-link closed-loop iteration is formed through the feedback optimization module, content supply, demand matching and experience presentation are changed into continuous optimization, and the problems that propaganda culture contents are similar and poor in interestingness are systematically solved.

The invention provides a dynamic data-driven adaptive content generation and risk control method and system and a medium, and the method comprises the steps: a data processing step: obtaining real-time dynamic data related to a specific theme, and processing the real-time dynamic data into structured data in a preset format; a preliminary content generation step: constructing a stylized model based on a preset style corpus, and generating preliminary content based on the structured data and the stylized model; a content adaptation step: acquiring a user portrait of the target user, and performing adaptation adjustment on the preliminary content according to the user portrait to generate adaptive content; and a risk verification processing step: before the adaptive content is output, carrying out risk verification on the adaptive content according to a preset risk rule base, and executing a preset risk disposal operation when a risk is verified. According to the method, personalized, adaptive and compliant high-quality contents can be generated in real time, the efficiency is improved, the risk is reduced, and the user experience is enhanced.

The invention discloses a cross-media content optimization method based on Internet promotion, which is characterized in that user characteristics and content requirements of different media platforms are deeply analyzed, a content form is customized, so that the content is closer to users, the attraction and the propagation effect of the content are improved, and a dynamic content adaptation technology is utilized to optimize the content. The optimal display effect of the content in different devices and different network environments is ensured, smooth and seamless user experience is provided, content experience is enhanced through the AR / VR technology, the participation degree and immersion of users are improved, a cross-media interaction guide mechanism and a social fission excitation mechanism are designed, user stickiness is increased, and user experience is improved. The social fission of the content is realized through the spontaneous propagation of the user, the brand influence and the user basis are expanded, the scheme forms a complete cross-media content optimization system, and through the systematic strategy and execution, the orderly proceeding of the promotion activity is ensured, and the maximum benefit of the brand in the Internet promotion and publicity is realized.

The invention discloses an intelligent interaction system based on an APP five-network-in-one technology and an implementation method, relates to the technical field of information interaction, and realizes deep fusion and intelligent interaction of multiple network ends (APPs, applets, H5, PC websites and V stations) through layered architecture design (a unified service support layer, a data cooperative processing layer, an intelligent adaptation interaction layer and a multi-network cooperative optimization layer). The system constructs a unified API gateway based on a micro-service and containerization technology, integrates multi-network-end data through an ETL technology, and realizes real-time synchronization by using a message queue; the intelligent terminal detection module and the AI interaction engine are combined with user equipment characteristics and behavior data to dynamically adjust page layout and generate a personalized strategy; the multi-network collaborative optimization layer promotes functional complementation, content adaptation and video propagation optimization. The problems that a traditional system is scattered in data, poor in collaboration and insufficient in intelligent interaction are solved, and the continuity of user cross-end experience is remarkably improved.

The invention relates to the technical field of advisement player management, and discloses an AI indoor and outdoor advisement player management system based on virtual reality. An environment sensing module of the system obtains indoor and outdoor environment parameters and user interaction data of an advertising machine deployment scene, and extracts spatial layout features and dynamic behavior features; the content adaptation module is used for matching advertisement content library candidate materials and generating a content adaptation scheme in combination with a delivery strategy; the virtual reality mapping module converts the scheme into a three-dimensional advertisement model and adjusts rendering attributes according to scene illumination and view angle parameters; the abnormity monitoring module collects running state data in real time, and analyzes deviation from a preset reference parameter to identify hardware or content playing abnormity; and the cloud collaboration module uploads the exception to the cloud analysis platform, receives the exception handling strategy and synchronously updates the local content library and the delivery strategy library. According to the system, the advertisement adaptability and the display effect can be improved, and the equipment management efficiency is optimized.

A method provides techniques for generating dynamically adapted content from received source content based on cultural and other differences and user / device presentation preferences. The method includes obtaining source content from a source application. The method further includes identifying one or more items of convertible information within the source content, and determining characteristics that can be correlated to device presentation preferences for presenting the source information in a format / style that matches the device presentation preferences. The method further includes creating a modified version of the source content with the at least one of the one or more items of convertible information converted to its renderable presentation alternative for presentation on the electronic device, and presenting the modified version of the source content via an output device such as an electronic display or audio speaker.

The invention provides an electronic bidding document generation method and system based on artificial intelligence, and the method comprises the steps: firstly obtaining a bidding demand text issued by a bidding party, a historical bidding document material set accumulated by a bidding party, and bidding demand change records of similar projects in an industry; and constructing a bid inviting scene semantic map containing demand nodes, multi-modal material nodes, trend association nodes and inter-node dynamic semantic association strength information. Generating an electronic bidding document dynamic framework according to the bidding scene semantic map, and calling a cross-modal artificial intelligence content generation model to generate a multi-modal module content first draft of each function module unit; and then semantic consistency adjustment and connection optimization processing are carried out on the first draft of the multi-modal module content to obtain the integrated multi-modal electronic bidding document content. And finally, in combination with the presentation specification information and the industry bidding preference data, carrying out structural typesetting optimization and content adaptation adjustment processing on the integrated content to obtain a final multi-modal electronic bidding document, so that the quality and pertinence of the electronic bidding document are remarkably improved.

To provide a system.SOLUTION: A system includes means for specify what is to be decided in a meeting, means for creating an agenda, selecting necessary members and adjusting schedules based on the specified content, means having timekeeper and facilitator functions to efficiently proceed with the meeting, means for taking minutes of conversations during the meeting and organizing decisions and next actions, and means for sharing the minutes.SELECTED DRAWING: Figure 1

The invention discloses an immersive cinema dynamic content adaptation control method based on multi-modal fusion, and the method comprises the steps: collecting at least one non-contact physiological signal of a target audience seat area in real time, the physiological signal comprising a respiratory wave signal collected by a millimeter wave radar or a photoplethysmography signal collected by a near-infrared photoelectric sensor; performing time-frequency analysis on the physiological signal, and extracting a physiological wake-up characterization value in a current time window; the physiological wake-up characterization value comprises a heart rate variability change rate and a heart rate deviation value; constructing a dynamic damping adjustment model, and calculating a virtual damping coefficient of the seat movement system at the current moment based on the physiological wake-up characterization value; and the virtual damping coefficient is converted into an execution instruction of a seat motion controller, and damping force output of the motion platform is adjusted in real time. The technical problem that the pre-programmed motion feedback is disjointed with the real-time physiological and psychological state of the audience can be solved, the experience adaptability and comfort of the cinema seat are improved, and the system safety is improved.

The invention provides a family-centered child development platform designed to support and enhance a child's academic, emotional, social, and cultural growth. By utilizing an AI-driven system for personalized learning, immersive VR / AR technologies for engaging educational experiences, and a community-building module for peer interaction, it offers an integrated solution for holistic child development. The system incorporates emotion detection, biometric feedback, and emotion-driven content adaptation, which dynamically adjusts the child's learning experience based on real-time emotional and physiological data. Additionally, the platform features culturally relevant content, promotes intergenerational collaboration, and includes a gamified learning environment to foster motivation and engagement. A secure interaction system ensures safe online communication, while the adaptive challenge system maintains an optimal level of difficulty tailored to the child's evolving needs. By combining these technologies, the platform provides a personalized, interactive, and supportive learning journey for children, supported by parents and educators.

The invention relates to the technical field of advertisement management, and discloses an advertisement publishing informatization management system and method, and the method comprises the steps: firstly obtaining the advertisement content uploaded by a user and a target distribution platform list, extracting the content specification requirements of each platform, and then carrying out the informatization management of the advertisement publishing based on the platform content specification requirements of each target distribution platform; and performing semantic detection on the advertisement content to obtain a semantic detection result. If it is found that the copywriting is not matched, content adaptation enhancement is carried out on the advertisement content to obtain the adaptive advertisement content, and it is ensured that the advertisement content keeps high-quality expressive force while meeting the platform specification. Finally, automatic release of the adaptive advertisement content is realized, and the efficiency and accuracy of advertisement release are remarkably improved. According to the method, the advanced natural language processing technology is integrated, unified management across multiple platforms is supported, the complexity and error rate of manual operation are reduced, the method is suitable for enterprises and individuals who need to efficiently and accurately publish advertisements, and the advertising industry is promoted to develop towards the intelligent direction.

Systems and techniques are provided for adapting digital content. For example, a process can include obtaining a digital content comprising a default configuration for outputting the digital content to a device; outputting, by the device, the digital content based on the default configuration for outputting the digital content. The process can include obtaining, from a monitoring engine, content interaction information associated with outputting, by the device, the digital content based on the default configuration for outputting the digital content. The monitoring engine is configured to monitor one or more interactions between one or more users of the device and the digital content. The process can include generating, based on the content interaction information, a content adaptation for the digital content. The process can include outputting, by the device, the content adaptation for the digital content.

The invention relates to an audio data processing method and device, a storage medium and a computer program product. The method comprises the steps that to-be-processed audio data in an online conference and key information of the online conference are acquired; based on the key information, determining first key content matched with the key information from the to-be-processed audio data; and adjusting an audio playing parameter of the first key content to obtain pre-processed audio data, and sending the pre-processed audio data to a terminal. The adjusted audio playing parameter can be used for highlighting and playing the first key content in the preprocessed audio data. In this way, the user can determine the key part in the conference at the first time, the situation that the user misses listening can be avoided, and then the effect of the online conference can be improved to a great extent.

Embodiments of the disclosure include a method of presenting a video stream that is to be received by a plurality of content consumers, comprising: receiving, by a first electronic device used by a content consumer, the video stream; collecting, by a first processor coupled to a first program of the first electronic device, content consumer data corresponding to the content consumer that is receiving the video stream; receiving, by the first program, the content consumer data; sending, by the first program, first instructions based on the content consumer data to the first processor; and updating, by the first processor, an audible or visible characteristic of the video stream being provided to the content consumer based on the sent first instructions.

The invention relates to a short message content AI iteration method and system based on user feedback, and the method comprises the steps: analyzing the keyword dispersion degree and reference content offset of a short message currently input by a user and a historical record, judging the dialogue interruption condition in combination with a timestamp, and dynamically adjusting a theme boundary and an information attenuation weight; a weighted sorting algorithm is adopted to optimize a historical reference sequence, semantic similarity is calculated, information retention weight is dynamically adjusted, and context coherence representation is enhanced; analyzing user intention rework content in AI feedback, adjusting an information attenuation weight, updating a dialogue state vector, calculating a theme drift risk value, and determining context association output adaptive to an interrupt scene; processing the optimized historical reference sequence according to a context association result and coherence representation, judging semantic consistency of reply contents, and outputting a target dialogue reply text; by analyzing the currently input short message of the user and various historically recorded indexes, the dialogue continuity and the user experience in the interruption restart scene are improved.