8 results about "Information overload" patented technology

The application discloses a kind of live content auditing method and system based on AI, belong to network live content supervision technical field.The method extracts the multi-dimensional characteristics of anchor by cognitive consistency analysis model, calculates the deviation degree of feature correlation matrix to detect cognitive dissonance;Adopt optical flow tracking and LSTM network analysis microexpression infers implicit intent;Monitoring semantic trajectory drift identifies sensitive content;Construct audience group dynamic graph to analyze emotional transmission intensity;Through bayesian network, from audience abnormal reaction, deduce illegal behavior;Evaluate cognitive load to identify information overload cover;Calculate node centrality to implement transmission blocking;Fusion multi-source information outputs rule determination.System includes cognitive feature analysis, microexpression identification, semantic trajectory monitoring, emotional transmission analysis, reverse reasoning, cognitive load calculation, transmission blocking and decision output eight modules, work cooperatively through event-driven mechanism.The application breaks through the surface limit of traditional audit, can identify cognitive fraud, psychological manipulation and other hidden violations, realizes active defense.

The invention discloses a multi-person picture synthesis method and device, equipment and a medium. The method comprises the following steps: splicing original images at multiple angles to obtain a panoramic image of a current target area; real-time tracking is carried out according to all face position information in the current frame, sound source information is collected synchronously, and a current spokesman in the target area is determined; and generating a multi-person synthetic picture according to the real-time motion picture of the current spokesman and the real-time motion pictures of other people. Multi-angle images are collected for feature point matching and image splicing, a high-quality panoramic image is generated, wide-area visual angle coverage is achieved, a more detailed image is obtained, all face positions are locked, corresponding sound source information is collected, a current spokesman is recognized, a multi-person synthetic picture which highlights the current spokesman and gives consideration to other people is generated, and the multi-person synthetic picture is obtained. The integrity of the panoramic information is guaranteed, meanwhile, the key content is clearly presented, the problems that the visual angle is limited and information is overloaded are solved, and the communication efficiency and watching experience of a teleconference are improved.

The application provides a robot cluster knowledge sharing method with body perception driving, belonging to the technical field of computer data processing, and generating a verifiable knowledge unit with a perception fingerprint containing sensor modalities and state parameters according to the perception data and task state of the robot. Through the on-demand accurate allocation of communication and computing resources, the overall operation efficiency of the robot cluster is greatly optimized, the passive global information broadcast is changed into the active knowledge acquisition of the robot individual based on the task demand, and the metabolic fusion mechanism based on the trust chain is combined to ensure that each robot only processes the most critical and most credible information for the current task, avoids information overload, significantly reduces the network bandwidth and individual processor load, and provides support for the deployment and application of large-scale robot clusters.

The application provides a user feature and external source double-engine pre-reasoning recommendation method and system, relates to the technical field of intelligent recommendation, user intention modeling and information pushing. The method and system fuse user instant context and long-term features to generate an IDR snapshot, simultaneously perform structured analysis on a preset high-value external source to generate a source event object, perform cross-space matching by a double-engine matching module, and write a candidate event into a candidate pool; before pushing, the pre-reasoning recombinant module performs abstract compression, cross-source splicing, conflict resolution and action suggestion generation on the candidate event, and outputs a pre-reasoning recommendation card after cognitive processing; finally, the active pushing arrangement module selects the best pushing strategy in combination with interruption cost and timing window; the upgrade from original material distribution to pre-reasoning cognitive card pushing is realized, the user secondary screening and processing cost is significantly reduced, and information overload is alleviated.

The present application relates to resource scheduling technical field, specifically to the innovative resource self-organizing scheduling method based on ant colony cooperation and bayesian learning, including the following steps: S1, factor space state variable initialization; S2, structured reading of public clues; S3, probabilistic inference of opportunity credibility.The present application combines the decision-making and collaborative behavior of individual innovation subjects, uses dynamically updated public clues, opportunity credibility inference, subjective value evaluation and dynamic depiction of collaboration threshold, effectively optimizes resource allocation and collaboration mode, improves decision-making efficiency through bayesian inference in practical application, reduces the negative impact of information overload, and ensures efficient collaboration when the project scale expands through the introduction of synergistic effect and immediate adjustment mechanism, enhances the adaptability and continuous optimization ability of the system through the endogenous decay of feedback mechanism and environmental memory, thereby improving the utilization efficiency of innovative resources and the success rate of project execution.

This invention discloses a consensus decision-making method, system, and storage medium based on distributed feedback, belonging to the field of internet collaborative decision-making technology. The method constructs a fully implicit autonomous decision-making system, including: collecting feedback data from network nodes on a target object; weighting the feedback data based on the implicit real-time reputation weights of the nodes to generate a consensus quantification result; silently updating the system state of the target object according to the consensus quantification result; and dynamically and silently adjusting the implicit reputation weights of the nodes in the background according to the state update result. This invention severs the direct causal chain between the perceptible behavior of nodes and system feedback, encapsulating consensus decision-making as a background environmental law unknown to the nodes. This fundamentally reduces the motivation for strategic gaming and malicious attacks by nodes, thereby improving the system's anti-attack capability, stability, and decision quality. It achieves game-resistant, self-stabilizing, and sustainably optimizing group decision-making, effectively solving governance problems such as information overload and the proliferation of low-quality content in large-scale digital communities.

This invention proposes an intelligent recommendation method and system for internet information streams based on multimodal data fusion. The method includes: acquiring candidate content and generating a multimodal fusion representation vector and information consumption; constructing a session semantic state vector and session attention bandwidth based on the features, consumption, and dwell time of content already displayed in the user session window; calculating the semantic similarity and consumption difference between candidate content and the current session to generate a unified recommendation bias; and generating a recommendation list by filtering target content based on the recommendation bias, under the constraint that the cumulative consumption does not exceed the attention bandwidth. This invention effectively prevents information overload and significantly improves the accuracy of recommendations and user experience by quantifying user attention bandwidth and combining multimodal features with content complexity for dynamic constraint sorting.

This invention belongs to the field of operation and maintenance visualization technology, and discloses a method and device for visualizing urban operation and maintenance situation based on multi-source data fusion. The method constructs a fused situation data set with situation objects as basic units, and generates semantic roles, display priorities, and time-effect decay visualization constraints for the situation objects. Combining the spatial distribution, quantity density, semantic co-occurrence relationships, and dynamic update characteristics of situation objects, a visual conflict degree evaluation model is established to quantify the degree of visual resource occupation by the current visualization interface. When the visual conflict degree reaches a preset condition, by identifying the emergency response stage, the situation objects are semantically graded and their visualization constraints are dynamically adjusted, achieving graded release and adaptive presentation of situation information under different emergency stages. This invention can effectively alleviate the information overload problem in emergency response scenarios, highlight key information, and improve the efficiency of urban operation and maintenance situation awareness and decision support.