10 results about "Web analytics" patented technology

The invention discloses an equipment health state monitoring method and system based on the Internet of Things. According to the method, data in a multi-source sensor is obtained and preprocessed, a real-time operation data set of equipment is obtained, and a health quantification deviation value and a health state trend are determined through the real-time operation data set. And when the health state is abnormal, recording a starting point coordinate of an abnormal event, marking an abnormal event triggering timestamp, and analyzing the dependency relationship between the equipment by utilizing graph network modeling. Furthermore, the potential risk probability is analyzed through the long-short-term memory network, real-time monitoring, fault propagation prediction and risk assessment of the equipment health state are achieved, and the operation reliability and the maintenance efficiency of the industrial equipment are improved.

The invention provides a personalized image content generation and optimization method and system fusing generative AI, and relates to the technical field of AI. The personalized image content generation and optimization method comprises the steps of analyzing a historical interaction track and a current intention expression of a target user based on a deep perception network, and constructing a multi-dimensional behavior portrait; user groups with similar generation preferences are identified by using a group feature recursive quantization technology, and a group wisdom feature map is constructed; performing multi-level mapping analysis on the user features and the group wisdom feature map, anchoring the group affiliation relationship of the target user and concretizing the guide features; constructing a multi-level guide vector according to current intention expression and guide features, performing accurate mapping on hidden space expression of an image generation model, quantizing deviation in real time and triggering intelligent calibration; and reconstructing a group distribution structure based on the evaluation data of the target user to realize dynamic evolution of the features. According to the invention, personalized demands of users can be accurately grasped, and the accuracy of image generation and the satisfaction degree of the users are improved.

Various embodiments of the present technology generally relate to systems and methods for providing an analytics engine. In an aspect, a method may be provided that includes receiving, by an analytics engine, a user query from a client device via a virtual assistant application hosted by a web-based application, where the web-based application includes various user interface (UI) elements, each of which is assigned to a respective event tag. Responsive to receiving the user query, the analytics engine may determine a first event tag based on the user query, where the first event tag is associated with a first UI element on the web-based application. The analytics engine may tag the user query with the first event tag to associate the user query with the first UI element and transmit a first report including the first event tag to a web analytics system associated with the web-based application.

A method for semantic perception editing of objects in a three-dimensional scene includes steps as follows: input point cloud data of a three-dimensional scene is analyzed by using a three-dimensional instance segmentation network, and a current position and a bounding box of a target object are determined based on an editing instruction. A set of semantic relationship rules between the multiple object instances from a historical editing case database is learned by using a Bayesian dynamic updating mechanism, and dynamic semantic constraints are dynamically generated. Editing operations are converted into a standardized mathematical representation by using a unified parametric framework, and the verified editing operations are optimized based on a comprehensive loss minimizing function to obtain optimized editing parameters. The three-dimensional scene is transformed based on the optimized editing parameters to obtain the edited three-dimensional scene.

The invention provides a social network user personality detection method based on multi-view feature fusion, and the method comprises the following specific steps: firstly, extracting semantic features of a posted text released by a user based on a pre-training language model, and carrying out the sentiment analysis of the posted text in combination with an external sentiment knowledge base, so as to form initial posted text embedding; thirdly, constructing a poster-personality trait heterogeneous graph, setting node interaction of three levels, and extracting multi-level interaction features by using a graph attention mechanism; furthermore, a multi-instance gating loop unit is introduced to model a user post sequence, time sequence features under different personality traits dimensions are captured, and information sharing among personality traits is promoted through an interactive attention layer. And finally, fusing the disordered interaction features and the sequence features, predicting personality characteristics of the user in multiple dimensions, and forming a comprehensive personality portrait. According to the method, the personality characteristics of the user can be comprehensively described, and the method is suitable for scenes such as personalized recommendation, user portrait construction, social network analysis and psychological health auxiliary diagnosis.

The application discloses a kind of based on the equipment health state monitoring method and system of Internet of Things.The method is by obtaining the data in multiple source sensors and pre-processing, obtains the real-time running dataset of equipment, determines health quantitative deviation value and health state trend by real-time running dataset.When health state is abnormal, the starting point coordinate of abnormal event is recorded and marked abnormal event trigger timestamp, and the dependence relationship between devices is analyzed using graph network modeling.Furthermore, the potential risk probability is analyzed by long short-term memory network.The application realizes real-time monitoring of equipment health state, fault propagation prediction and risk assessment, and improves the operation reliability and maintenance efficiency of industrial equipment.

The application discloses a kind of social group member dynamic management method and system, it is related to social network analysis field, including, the online interaction data and offline co-occurrence data of social group member are acquired, and are washed, the online interaction data and offline co-occurrence data after washing are converted into structured data set;Structured data set is imported into graph database to obtain initial weight, and dynamic attenuation weight is calculated, and basic relationship network is constructed;The edge weight matrix in basic relationship network is converted into quantum bit entanglement state, quantum bit entanglement state is measured to form quantum probability amplitude, quantum entanglement determination threshold is set, and quantum relationship thermodynamic diagram is generated by Grover algorithm.The application realizes the accurate management and risk prevention and control of social group member relationship by the technical scheme that quantum computation is combined with dynamic entropy analysis, the edge weight matrix of basic relationship network is converted into quantum bit entanglement state, and quantum relationship thermodynamic diagram is generated using quantum measurement and Grover algorithm.

The application provides a personalized image content generation and optimization method and system based on fusion generative AI, relates to the technical field of AI, and comprises the following steps: analyzing the historical interaction track and current intention expression of a target user based on a deep perception network, and constructing a multi-dimensional behavior portrait; identifying a user group with similar generation preferences by using group feature recursive quantization technology, and constructing a group wisdom feature map; performing multi-level mapping analysis on the user features and the group wisdom feature map, anchoring the group affiliation of the target user and visualizing the guide features; constructing a multi-level guide vector according to the current intention expression and the guide features, accurately mapping the hidden space representation of an image generation model, quantifying the deviation in real time, and triggering intelligent calibration; and reconstructing the group distribution structure based on the evaluation data of the target user, and realizing dynamic evolution of the features. The application can accurately grasp the personalized needs of users, and improve the accuracy of image generation and user satisfaction.

The invention relates to the field of account qualitative analysis, in particular to a social media account qualitative analysis method. The method comprises the following steps: performing multi-dimensional feature extraction on a social media account, constructing comprehensive feature representations of the social media account, and performing fusion calculation on a plurality of comprehensive feature representations; step 2, based on a Double DQN reinforcement learning method, adaptively optimizing the weight of the comprehensive feature of the social media account; step 3, deep time sequence feature learning is realized through an LSTM-GRU hybrid network architecture, a time sequence is predicted, abnormal fusion data is detected through a variational auto-encoder, and network parameters are optimized; 4, performing deep social network analysis on the social media account, performing node representation learning and influence propagation modeling through a GraphSAGE method, and verifying propagation prediction data; and 5, evaluating the propagation prediction data through a multi-dimensional evaluation system to obtain a qualitative analysis result of the social media account.

The invention provides a DDQN-based social network viewpoint polarization and divergence intervention improvement method, and belongs to the field of social network analysis. The method specifically comprises the following steps: initializing an initial viewpoint of a social network, simulating interactive updating between users by adopting a Friedkin-Johnsen model, and calculating an initial divergence value and a polarization value of the social network after an iteration number moment reaches a stable state; designing an intervention agent, selecting some users, modifying viewpoints of the users, and calculating a divergence value and a polarization value after intervention after a stable state is reached through iteration for several times; a DDQN model is adopted, a state vector of a user is input, and an optimal intervention strategy is learned by taking maximization of a divergence value and a polarization value of the social network as a target; and training the model to achieve an optimal intervention strategy. According to the method, polarization regulation and control with low interaction cost are realized through modular design, different network topologies can be flexibly adapted, and technical reference is provided for dynamic intervention of social network opinions.