122 results about "User analysis" patented technology

A multi-node, multi-container cluster system that generates, aggregates, and manages log files from services and components to be used for audit logs and to debug and perform other serviceability tasks provided by a vendor of the cluster system. Logs are collected from all components of the system and aggregated into a consistent format for user analysis and debugging. Embodiments provide a comprehensive way to parse and index vast numbers of log files that can then be packaged and displayed to a user in a way that facilitates analysis and debugging and / or efficient input to appropriate debugging programs.

The invention belongs to the technical field of data security, and particularly relates to a data security protection system and method based on multi-dimensional factors. Comprising a user analysis module, an environment risk analysis module, a data sensitivity grading module, a behavior analysis module, a risk assessment module and a decision execution module. The method has the beneficial effects that aiming at the defects of a traditional static permission model, a dynamic risk assessment system is constructed by fusing user identity, behavior pattern, access context and environment security four-dimensional features in combination with reinforcement learning weight optimization, and the problem that the permission cannot be adjusted in time when the user behavior is abnormal is solved; according to the method, the problems that multi-dimensional information such as environment, behavior and data sensitivity is not fused, data leakage or unauthorized access risks cannot be recognized in real time and the like are solved, sensitive data exposure risks can be effectively reduced, meanwhile, the problem that a static permission model cannot respond to behavior / environment changes in real time is solved, and enterprise data security is improved.

The invention discloses a data analysis method and device, equipment and a storage medium, and relates to the technical field of data analysis, and the method comprises the steps: analyzing a user analysis demand according to a data big model and prompt word information corresponding to a preset grammar rule, and obtaining a demand operation type and a data processing sequence; performing instruction generation according to a preset grammar rule, the demand operation type and the data processing sequence to obtain a domain-specific language; and analyzing the to-be-analyzed data according to the domain-specific language and the data analysis engine to obtain a target data analysis result. Complex data analysis and visualization requirements of a user are expressed in a concise language description through a set grammar rule, a large model only needs to generate a domain-specific language, and then the domain-specific language is analyzed by an analysis engine, so that the use cost of the large model is reduced, and meanwhile, the data analysis efficiency is improved.

The invention discloses an EEG intelligent agent automatic analysis method based on a large language model, which takes the large language model as a strategy engine, autonomously understands user analysis intentions and intelligently decomposes tasks, and further dynamically schedules and collaboratively integrates analysis resources including traditional feature engineering, diversified deep learning models and an external knowledge base. According to the method, end-to-end automatic coordination and execution of complex EEG analysis tasks such as signal preprocessing, feature extraction, event positioning, classification diagnosis, emotion recognition, sleep staging and the like can be realized, the limitation of a single detection or classification task is broken through, and through context perception and flexible space-time analysis capability, the accuracy of the EEG analysis is improved. And multitask and continuous deep reasoning and interpretation can be carried out on the complex EEG data. According to the method, the general planning and reasoning capability of a large language model is deeply fused with a special analysis model in the EEG field, so that the automation level, flexibility and clinical application potential of EEG analysis are remarkably improved.

The invention relates to the technical field of commodity data management, in particular to a commodity recommendation method based on a multi-agent model. The multi-agent model comprises a main agent, at least one user analysis sub-agent and a plurality of category exclusive commodity analysis sub-agents. The method comprises the following steps: the main agent collects commodity demand information of a user; the main agent analyzes the commodity demand information to determine the category span of the user demand, and judges whether the user demand is a cross-category demand; and if the demand is a cross-category demand, the main agent activates a commodity analysis sub-agent of a corresponding category according to a category span, and sends user demand feature data generated by the user analysis sub-agent to the activated commodity analysis sub-agent. Through a multi-agent model technology of overall planning of the main agent and division and cooperation of the sub-agents, accurate matching of cross-category and single-category demands, efficient utilization of resources and flexible service adaptation are realized, and finally the commodity recommendation accuracy is improved.

A system for data aggregation from at least one source for use in data analysis having a graphical user interface that shows multiple data sources for users to analyze data. A database stores and visualizes data from data files captured on a web application, whereby users analyze the data through visual tools, charts, and graphs. The system also automatically transforms the data into evaluation templates. The evaluation templates may be an automated computer readable format. The reports can be customized by users or selected from existing templates. Users have the ability to design their own reports.

The invention discloses an English reading ability training system and method based on artificial intelligence, and aims to solve the problems of insufficient personalization, poor interactivity, feedback lagging, imperfect evaluation system and low resource matching degree in an existing English learning platform. The system comprises a data acquisition module, a user analysis and personalized path planning module, a dynamic content generation and practice design module, a real-time monitoring and feedback adjustment module and a comprehensive evaluation and report generation module. Basic information and real-time feedback of the user are collected, learning characteristics, interests, preferences and ability levels of the user are accurately identified by using a machine learning algorithm, and a personalized learning path is provided for the user; meanwhile, natural language processing, machine learning and text generation technologies are integrated, and reading materials meeting user requirements are dynamically generated; analyzing the comprehensive difficulty of the generated material by utilizing a machine learning algorithm, wherein the comprehensive difficulty is quantified by adopting a text comprehensive difficulty score TCS; reading understanding exercises including vocabularies, grammar, reasoning and critical thinking are provided, and the subsequent exercise difficulty is intelligently adjusted based on user performance data so as to optimize the learning effect. The system also continuously tracks user performance data, analyzes progress and problems through a machine learning algorithm, improves the regular evaluation capability, automatically adjusts a learning path and a material strategy, and periodically generates a multi-dimensional comprehensive evaluation report.

To provide a method for multilaterally evaluating the skill of registered personnel.SOLUTION: In a user evaluation method for evaluating a user, a system executes an input information receiving step of receiving input information including information on a biography of the user, a question output step of creating a question based on the input information using the input information and outputting the question, a response receiving step of receiving response information from the user regarding the question, and a user analysis step of analyzing a feature of the user based on the input information and the response information and obtaining analysis information of the user.SELECTED DRAWING: Figure 2

The application provides a network user intention recognition method, vectorization representation of text content and emotion is realized through two kinds of Bert pre-training models, efficient extraction of global and local features of the text is realized by adopting a Text-Inception module and a Bi-LSTM network, further, dynamic fusion of the local features and the global features of the text is realized based on an improved SENet network, and dynamic combination of the text and emotional features is realized through a residual cross-attention mechanism, understanding and recognition of the intention of the social network user are realized. Finally, the application can accurately recognize the intention of the user, and further provide support for a wide range of application scenarios, such as malicious user analysis of social media.

An apparatus and method of user analysis and content selection comprising: for a population of other users that have completed a particular game objective: determining a plurality of game objective completion time deciles for a predetermined number of other game objectives previously completed, deriving a representative completion time decile from the plurality of game objective completion time deciles, using the representative decile value as an input variable and a corresponding game objective completion time for the particular game objective as an output variable, generating a time band classification; for a particular user: determining a game objective completion time decile for a predetermined number of other game objectives completed by the particular user, deriving a representative completion time decile from the plurality of game objective completion time deciles, and using the representative completion time decile as an input to the generated time band classification, identifying a time band classification for the particular user; and outputting predicted game objective completion time data for the particular game objective based on the identified time band classification for the particular user.

An object of the system according to the embodiment is to efficiently generate an advertisement creative with a high CTR or CVR and display an optimum advertisement for each user.SOLUTION: A system according to an embodiment includes an advertising creative analyzer, a generator, and a user analyzer. The advertising creative analysis unit analyzes an advertising creative with a high CTR or CVR. A generation unit generates a new advertising creative based on the features analyzed by the advertising creative analysis unit. The user analysis unit analyzes the advertising creative generated by the generation unit for each user and displays an optimal advertisement.SELECTED DRAWING: Figure 1

This invention discloses a news retrieval question-answering method and system based on a large language model (RAG), relating to the field of large language model text generation technology. It performs intent understanding on user questions and provides a news retrieval question-answering method based on a large language model. This method enhances the comprehensiveness of search results and final answers by increasing data sources and expanding the query scope; accurately grasps user intent and correctly identifies and uses parts of the search results relevant to the user's question to improve the accuracy of the answer; answers questions in a progressive manner and provides an intuitive display of the event timeline to help users analyze the development of events.

The invention discloses an experimental data analysis method, device and equipment and a storage medium, and relates to the field of data processing, and the method comprises the steps: carrying out the demand analysis of an experimental data file and a user analysis demand based on a large language model, and determining an experimental task specification which at least comprises an experimental type; according to the experiment type and the experiment data file, generating a standardized data table and a data portrait; determining an experimental data analysis plan according to the experimental task specifications and the data portraits; executing an experimental data analysis plan, and performing data processing on the standardized data table to obtain cartographic data and a statistical analysis result; based on a decoupling mechanism of drawing code generation and execution, generating experimental chart data according to the drawing data; and generating an experimental data analysis report according to the experimental chart data and the statistical analysis result. According to the scheme, end-to-end experimental data analysis from data input to report generation is realized, and the accuracy of experimental data analysis is improved.

Disclosed is a system (200) and method (300) for visualizing performance metrics data of wireless devices (106-118) within a selected viewport on a map interface. The method involves displaying a graphical user interface (GUI) with selectable options for defining a viewport and a service area of interest in a map layer. Further, upon receiving the user's input, relevant device data and network performance data of each wireless device within the selected viewport and the service area of interest is retrieved. The retrieved data is processed to generate the performance metrics data in a tabular format indicating a mapping of the device data with the network performance data corresponding to each wireless device. Further, the GUI provides options for sorting, filtering, downloading, and sharing the performance metrics data to facilitate detailed user analysis.

A system is provided.SOLUTION: A system comprising: input means for receiving data of income, expenditure, and saving target input by a user; transmitting means for transmitting the data from the input means to a server; storing means for storing the data received from the transmitting means in a database in the server; analyzing means for analyzing the data stored in the storing means and generating optimum household economy management advice in the server; and notifying means for notifying the user of the household economy management advice generated by the analyzing means.SELECTED DRAWING: Figure 1

The embodiment of the invention discloses a method and device for obtaining a function call sequence of a process and electronic equipment, relates to the technical field of computer application, and aims to provide convenience for a user to analyze the process. The method is applied to a Linux system, and comprises the following steps: receiving an acquisition instruction of a kernel mode function call sequence of a specified process; the acquisition instruction comprises an identifier of the specified process; according to the acquisition instruction, acquiring a kernel mode function call sequence of the specified process; determining management information corresponding to the specified process according to the identifier of the specified process; determining a user mode function call sequence of the specified process according to the management information corresponding to the specified process; and combining the kernel mode function call sequence with the user mode function call sequence to obtain a function call sequence of a full chain of the specified process. The method and the device are suitable for analyzing the user process.

The invention discloses an intelligent power grid demand side management method, system and device based on user power consumption behavior analysis and a medium, and belongs to the technical field of intelligent power grids, and the method comprises the steps: obtaining original user power consumption data, building a power consumption behavior observation sequence based on the original user power consumption data, analyzing the electricity utilization behavior observation sequence to identify the electricity utilization behavior state of each user; based on the power consumption behavior state of each user, extracting historical power consumption records of each user from the original user power consumption data and response characteristics of the user load to the regulation and control instruction, and constructing a user analysis matrix; processing the user analysis matrix to obtain a subdivision result of the user group; and according to a subdivision result, determining key label values of load matching degree, adjustable potential and interaction willingness of each subdivided user group, and carrying out level-to-level management on the subdivided user groups by adopting a user grouping algorithm based on the key label values. Optimized operation and supply and demand balance of the intelligent power grid are realized.

The application discloses a user analysis method and device based on a large model, equipment and a storage medium, and relates to the technical field of user analysis.The method comprises the following steps: collecting cross-modal interaction data to construct a representation data set, calculating cognitive load and extracting an implicit aversion anchor point deviating from explicit feedback, optimizing a large model to generate a dynamic user representation through incremental adversarial training, and formulating a compensation strategy based on the cognitive dissonance theory.The device comprises a representation acquisition module, an anchor point extraction module, a model optimization module and a strategy formulation module.The equipment realizes the method steps by executing a program through a processor, and the storage medium stores a corresponding computer program.The application realizes the identification and active compensation of implicit aversion through multi-modal data fusion and dynamic modeling, can locate a user experience blind area, optimize interface interaction, improve recommendation accuracy, and optimize the implicit aversion perception ability of the large model.

The invention relates to the technical field of audio-video intelligent optimization, and discloses an integrated intelligent audio-video playing system, which comprises a content acquisition module, a user analysis module, a playing control module, an energy-saving optimization module, a state monitoring module, a cloud synchronization module and an emergency processing module, by setting an intelligent sensing module, when video content is played adaptively, personalized matching of video recommendation is ensured by formulating double analysis standards of user emotion and environmental parameters and setting differentiated recommendation thresholds for different scenes, and meanwhile, environmental noise and user physiological sensor data are collected in real time; therefore, interference factors and instant emotional states of the environment where the user is located can be dynamically perceived, the problem of recommendation dislocation caused by environment interference is eliminated, high conformity of played content and user requirements is guaranteed, and the recommendation error rate is reduced.

The application discloses a passenger car carbon emission monitoring and regulation system and method based on multi-source space-time data, comprising: a data fusion module for processing multi-source data and outputting space-time aligned fusion data; a carbon emission tracing and user analysis module for calculating vehicle-level carbon emission contribution and dividing user groups based on the fusion data; a multi-level regional accounting and early warning module for receiving and based on the vehicle-level carbon emission contribution and user group division results, and generating early warning signals by comparing preset targets; a regulation simulation and feedback module for simulating and generating regulation instructions according to the early warning signals, and feeding back the effect data after the instruction execution to the carbon emission tracing and user analysis module. The application realizes the tracing of massive mobile source carbon emissions from a macro region to specific vehicles, driving sections and time segments by constructing a data fusion-vehicle-level carbon emission calculation-user group clustering analysis chain, and solves the industry problem.

This invention belongs to the field of data analysis and query optimization technology. Specifically, it relates to an interactive, visual data analysis and dynamic query optimization system, comprising: a multi-source data aggregation module for extracting query feature sets from interactive query data; a feature extraction and construction module for building an interactive query prediction model based on the user's analytical intent and a pre-defined query optimization engine and query feature set; a model intent prediction module for outputting a dynamic query plan set based on the interactive query prediction model and establishing a switching mechanism; a plan generation and switching module for generating a dynamic analysis view set based on the query execution result set using a multi-version view adaptation strategy combined with the switching mechanism; and a view rendering and output module for optimizing rendering performance and incrementally updating the dynamic analysis view set, outputting a real-time responsive analysis visualization interface. This invention enhances the level of analytical intelligence and automatically and accurately identifies the user's true analytical intent.

Systems and methods described herein provide an application function and interface for a Network Data Analytics Function (NWDAF) to receive, from User Equipment (UE) devices, user data for edge applications. An NWDAF receives an analytics request for user analytics for an edge application and sends, to an Edge Analytics Engine (EAE) associated with an edge location, a data request based on the analytics request. The EAE receives user data from an Edge Enabler Client (EEC) on the UE device that is connected to the edge location. The EAE forwards the user data to the network device. The NWDAF receives the user data responsive to the analytics request and generates an analytics report based on the user data.

We provide the system. [Solution] The system includes an information processing device for generating a virtual reality environment, and the virtual reality environment includes means for reproducing a scene intended for tactical training of movement, A means for detecting the actions of participants within a generated virtual reality environment using a detection device and acquiring information related to those actions, A means for immediately analyzing the information obtained above and generating tactical feedback based on the analysis results, Means including a display device or output device for notifying the user of the analysis results, A means of monitoring user behavior and providing virtual exercise scenarios using a humanoid robot for home use, A system that includes this.

The embodiment of the invention discloses a wireless signal evaluation system. The system comprises at least one comprehensive signal analyzer and a remote terminal, the comprehensive signal analyzer comprises a spectrum analysis module, a map position module and an analysis training module, and the remote terminal is configured to obtain the equipment position information and the user information of the comprehensive signal analyzer through the map position module; determining candidate test parameters; based on the equipment position information of the comprehensive signal analyzer, the user information, the candidate test parameters and the grouping information of the comprehensive signal analyzer, determining the analysis difficulty of the candidate test parameters through a determination model; based on the analysis difficulty, simulation test parameters are determined, and the simulation test parameters are sent to the comprehensive signal analyzer; and in response to the obtained user analysis result of the comprehensive signal analyzer, determining a simulation test result based on the user analysis result.

The invention discloses a quail digital breeding data processing system based on terminal cloud collaboration, and belongs to the technical field of quail breeding. Quail breeding is monitored in real time, and breeding collection data is obtained; processing the culture collection data according to a preset data processing mode, and sending the processed culture collection data to a cloud platform; identifying analysis requirements of the user, and analyzing the breeding collection data according to each analysis requirement to obtain an analysis result of each analysis requirement; setting a traceability demand table, and performing real-time traceability analysis on the database according to the traceability demand to obtain each sharing management demand; processing the stored data of the database according to each sharing management demand; real-time, continuous and accurate monitoring of quail breeding environment parameters is achieved, any abnormal changes of key environment indexes such as temperature, humidity and ammonia gas concentration can be captured in time, and farmers can rapidly take effective adjustment measures.

The application discloses an experimental data analysis method and device, equipment and a storage medium, and relates to the field of data processing.The method comprises the following steps: based on a large language model, performing demand analysis on an experimental data file and a user analysis demand, determining an experimental task specification, and determining that the experimental task specification at least comprises an experimental type; generating a standardized data table and a data portrait according to the experimental type and the experimental data file; determining an experimental data analysis plan according to the experimental task specification and the data portrait; executing the experimental data analysis plan, performing data processing on the standardized data table, obtaining mapping data and statistical analysis results; based on a decoupling mechanism of mapping code generation and execution, generating experimental chart data according to the mapping data; and generating an experimental data analysis report according to the experimental chart data and the statistical analysis results.The application realizes end-to-end experimental data analysis from data input to report generation, and improves the accuracy of experimental data analysis.

The application discloses an EEG intelligent agent automatic analysis method based on a large language model, takes the large language model as a strategy engine, autonomously understands user analysis intentions and performs intelligent decomposition of tasks, and then dynamically schedules and cooperatively integrates analysis resources including traditional feature engineering, diversified deep learning models and external knowledge bases. The application can realize end-to-end automatic coordination and execution of complex EEG analysis tasks from signal preprocessing, feature extraction, event positioning to classification diagnosis, emotion recognition, sleep staging, etc., breaks through the limitation of single detection or classification tasks, and enables multi-task, continuous deep reasoning and interpretation of complex EEG data through context perception and flexible space-time analysis capability. The application deeply integrates the general planning and reasoning capability of the large language model with the special analysis model in the EEG field, and significantly improves the automation level, flexibility and clinical application potential of EEG analysis.

The utility model discloses a device for automatically monitoring effectiveness of a cathode protection system of a metal pipeline, which comprises a computer processor assembly, a sensor assembly, an electric data bus, a medium and a protected structure, a computer processor component connected to one or more sensor components placed along an electrical data bus, the sensor components and the electrical data bus being buried or submerged in a medium; the sensor assemblies are placed at a first distance of a protected structure, and adjacent sensor assemblies are separated by a second distance; according to the utility model, a user can be helped to analyze and check the performance of the cathode protection system, and data can be summarized regularly or at any random period so as to ensure the normal operation of the current cathode protection system.

The disclosed technology embodies beneficial methods of online task and motion planning for robots based on robot task decomposition into subtasks with additional features that indicate, among other things, whether dynamic trajectory correction is allowed during execution of the subtasks. Decomposition and feature marking enable hybrid motion control during task execution, for example, some subtasks allow reactive motion planning to be employed to avoid collisions, while other subtasks do not allow reactive motion to be employed. Collision avoidance of non-reactive subtasks involves, for example, coordinating volume reservation within the robot workcell involved to prevent other robots from interfering with the robots that are performing designated non-reactive subtasks. It is determined which sub-tasks are non-reactive dependent on information contained in the input task specification, and may be based on user analysis or automatic analysis of robotic applications involved.

The invention discloses a control system for a graphene far-infrared heating light wave room, which belongs to the technical field of light wave physiotherapy and comprises a graphene heating module, a data storage module and a user analysis module. The graphene heating module is used for emitting light and heating according to the received control parameters; the data reserve module is used for performing data reserve analysis, acquiring material data in real time, analyzing the material data, obtaining a plurality of user classifications and reserve parameter lists corresponding to the corresponding user classifications, and summarizing the user classifications and the reserve parameter lists to establish a reserve library; the user analysis module is used for performing real-time analysis on users in the light wave room according to the reserve warehouse, determining control parameters of the light wave room and sending the control parameters to the graphene heating module; through collaborative innovation of a graphene material and an intelligent control system, the technical contradictions of insufficient penetrability, low temperature control precision, high energy consumption and poor safety of traditional thermal therapy equipment are systematically solved.