31 results about "Knowledge base management systems" patented technology

The invention discloses a knowledge base management system and an enhancement method, and belongs to the technical field of data processing, and the method specifically comprises the steps: obtaining user query information containing a plurality of semantic elements, and determining an IT service scene according to the semantic elements and a pre-constructed IT service knowledge graph; dividing query information into a high-priority semantic information area and a low-priority semantic information area according to the dimension of the knowledge base; core knowledge is quickly positioned based on the high-priority semantic information region, and a retrieval result is perfected in combination with the low-priority semantic information region; if the semantic element has multiple semantics, triggering multi-semantic query; according to the method, the accuracy and efficiency of IT service knowledge retrieval and semantic understanding are effectively improved, and the application value of the knowledge base is enhanced.

The invention belongs to the technical field of database management, and particularly relates to a knowledge base intelligent management system and method based on a large model, and the system collects question and answer texts and index information of different target subjects through a data collection module, and generates a first text hierarchical sequence and a directed index graph through word segmentation preprocessing and directed graph neural network mapping; the feature extraction module extracts text and index embedding representation in combination with a feature distillation model, and obtains similar overlapping degrees of different target main bodies through a three-dimensional overlapping degree model; the conflict simulation module constructs an initial knowledge base based on a tree database, detects index conflicts in target subjects and among the subjects by using a Bayesian simulation algorithm, and generates a conflict risk list; the conflict resolution module outputs a resolution strategy in combination with a conflict resolution confrontation model, and the feedback adjustment module iteratively optimizes the knowledge base until a conflict threshold and a user demand are met; according to the method, intelligent management of cross-subject question and answer indexes is realized, and knowledge base conflict resolution efficiency and cross-subject query accuracy are improved.

The invention relates to the technical field of express service management, and discloses an express service problem solving method and system based on a knowledge base management system, and the method comprises the steps: firstly obtaining the form and semantic features of a package, obtaining an atlas node state matrix through the operation of structural analysis, abnormal mark matrix generation, mapping relation establishment and the like, and obtaining multi-stage calibration parameters according to the atlas node state matrix; constructing a cross-modal mapping function cluster to obtain a parcel feature matrix, designing a knowledge base retrieval sorting mechanism to generate a knowledge recommendation list, and finally generating a solution based on the list and feeding back the knowledge base; according to the method, through multi-modal data processing and application of the knowledge base, the accuracy and efficiency of express service processing are remarkably improved, the practicability and adaptability of the knowledge base are enhanced, and powerful support is provided for intelligent development of express services.

The invention discloses an intelligent document analysis method of a knowledge base management system, and relates to the field of artificial intelligence large model multi-modal analysis. Comprising the following steps: step 1, preliminarily identifying a document format according to a document extension name, and performing corresponding analysis according to the type of the document format: performing text analysis for pdf, docx, doc and txt document formats, and extracting texts and images in the pdf document format for the pdf document format; aiming at the docx document format, analyzing the compressed package in the docx document format according to the natural sequence of the document, and extracting a text and a picture; aiming at the doc document format, identifying and extracting all text information in the doc document format; for a txt document format, character codes are recognized and processed, and various languages and symbols are extracted; the method comprises the following steps of 1, analyzing a text, 2, processing the analyzed text by utilizing a large model, namely segmenting the text, performing vectorization processing, converting the text into a numerical form which can be understood by the large model, and storing the converted text in a knowledge base for information retrieval, data analysis and knowledge mining, and 3, performing visual output on the text at the same time.

The invention relates to an enterprise knowledge base management system and method, which comprises portal display, business processing, basic configuration and business support which are mutually connected through standardized interfaces and processes to form a complete and efficient knowledge management system. The system can reduce the problem of knowledge dispersion, improve the retrieval efficiency and quickly position the required information.

The invention relates to the technical field of knowledge management, in particular to a knowledge base management system based on artificial intelligence, which comprises a knowledge acquisition module, a knowledge arrangement module, a knowledge updating module, a knowledge recommendation module, a user interaction module, a knowledge security module and a system management module. The system automatically obtains and sorts structured and unstructured data from multi-source data, generates a knowledge graph and performs hierarchical classification. The content of the knowledge base is dynamically adjusted and updated through time sequence analysis and a self-adaptive updating mechanism, and personalized recommendation is achieved in combination with user behaviors and historical queries. The system adopts an advanced encryption standard and a role access control technology to ensure the security of the knowledge base, so that the knowledge acquisition, arrangement and recommendation efficiency is remarkably improved, meanwhile, the high availability and data security of the system are ensured, and the system is suitable for a large-scale knowledge management scene.

A method and a system for building a knowledge base for industrial use and using the knowledge base to manage and control industrial products, processes, resources and systems. The knowledge base uses semantic processing modules and artificial intelligence tools to enable continuous extraction and entry of knowledge into the knowledge base from various sources including user inputs, operation status reports, manuals, websites, diagnosis reports, sensor data, operation sequence, and other static or ephemeral sources. The knowledge base is supported by a knowledge base management system that includes a suite of tools to support knowledge entry, update, retrieval and visualization using both natural language based queries and structured queries with predefined syntax. The system also provides tools to retrieve and assemble knowledges on-the-fly to support industrial applications including to design products, services or production lines, build production process, manage scheduling and flow, monitor and optimize operations, diagnose issues, apply business logics, procure materials and supplies, manage and train workforce, and provide customer supports.

The invention discloses a design method of a multi-modal knowledge base management system, and relates to the technical field of database management systems. Comprising the steps of 1, establishing a knowledge base management system, 2, pushing corresponding modal data into a corresponding analysis module through an identification module according to a heterogeneous data source type, and 3, obtaining corresponding unstructured data from MinIO distributed storage service according to a storage path and semantic retrieval when a large model processing module is called, and obtaining corresponding characters from the knowledge base for common display.

The invention discloses a graph database-based production command knowledge base management system and method, and the method comprises the steps: constructing a production command knowledge graph database through employing a Neo4j graph database platform, extracting node semantic features and edge semantic features in the graph database through employing a deep learning technology, and meanwhile, carrying out the extraction of the node semantic features and the edge semantic features in the graph database; semantic optimization is performed on node features by taking significant semantic information of all edges connected with nodes as guidance so as to improve the expression ability of the node semantic features, and then fuzzy semantic matching is performed on user query intention description and the optimized node semantic features so as to improve the user query intention description and the user query intention description. Therefore, the node information related to the query intention of the user is intelligently returned as a query result. In this way, efficient management and intelligent query of production command knowledge can be achieved, the accuracy and correlation of query results are effectively improved, and query requirements in a production command scene can be better met.

The invention discloses a knowledge base-based sewage plant blower online diagnosis system and a knowledge base-based sewage plant blower online diagnosis method. The system comprises an edge-cloud collaborative architecture which is composed of an edge end deployed on an equipment site and a cloud server; the cloud server comprises a knowledge base management system, a hybrid inference engine and a model training platform; the problem of collaborative optimization of single information dimension, limited reasoning mechanism, knowledge update lag and response delay in sewage plant blower fault diagnosis is solved, and the method is realized by constructing a full-dimension knowledge base and combining an edge-cloud collaborative architecture and a rule-case-deep learning hybrid reasoning mechanism. The effects of fault diagnosis accuracy improvement, response speed acceleration and knowledge base self-evolution are achieved.

1. The name of the design product: knowledge base management system graphical user interface for electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: new energy photovoltaic material management system. 6. The human-computer interaction mode of the graphical user interface: in the front view, click the first "knowledge base" on the right side of the top menu bar to enter the interface change state diagram 1; click "role management" in the left menu of the interface change state diagram 1 to enter the interface change state diagram 2, and user settings personnel can be added, departments can be added, and management permissions can be edited. 7. Other circumstances that need to be explained: "X" in the interface represents replaceable text, numbers, letters or symbols, and the gray block is the replaceable content screen.

This invention discloses an enterprise intelligent knowledge base management system and method based on a vector model, relating to the fields of intelligent information retrieval and natural language processing. This invention parses unstructured documents in various enterprise formats, extracting semantic structure information such as text heading levels and paragraph boundaries, and segmenting them into a set of text fragments. The text fragments are then cleaned to obtain effective text fragments. These effective text fragments are integrated into semantic text blocks with the same topic. Sentence vectors are generated using a pre-trained semantic encoding model. Semantic segmentation points are located based on the semantic similarity of adjacent sentences to obtain standardized knowledge units. A dual-database collaborative query is constructed. After receiving user queries, structured pre-filtering is performed through a relational database, followed by semantic retrieval through a vector database. The intersection of the results from both databases is taken, and a comprehensive score is calculated based on multi-dimensional weights. After filtering, aggregation, and tracing, the results are output. If no matching results are found, a tiered fallback process is triggered, completing the entire retrieval loop.

The invention proposes an intelligent knowledge base management system, and relates to the technical field of knowledge maps, and the system comprises a knowledge map construction module which is used for constructing a hierarchical knowledge map; the scene sensing module is used for collecting scene features of the current operation state of the power grid in real time and fusing the scene features to obtain a scene embedding vector; the knowledge retrieval module is used for executing directional propagation in the hierarchical knowledge graph according to user query to obtain candidate knowledge nodes; the risk assessment module is used for calculating the overall risk of the candidate knowledge nodes based on the topological attribute vector and the scene embedding vector; the dynamic shielding module is used for shielding the candidate knowledge nodes of which the anti-fact risk differences exceed a risk threshold value to obtain the candidate knowledge nodes which are not shielded; and the recommendation output module is used for sorting the candidate knowledge nodes which are not shielded from low to high according to the overall risk and outputting the candidate knowledge nodes. According to the method, knowledge retrieval and recommendation which conform to a power grid operation rule and can avoid the situation that a scene depends on high-risk operation can be realized.

The application provides an intelligent knowledge base management system, and relates to the technical field of knowledge graph, which comprises a knowledge graph construction module, a scene perception module, a knowledge retrieval module, a risk assessment module, a dynamic shielding module and a recommendation output module; the knowledge graph construction module is used for constructing a hierarchical knowledge graph; the scene perception module is used for collecting and fusing the scene features of the current operation state of the power grid in real time to obtain a scene embedding vector; the knowledge retrieval module is used for performing directional propagation in the hierarchical knowledge graph according to user query to obtain candidate knowledge nodes; the risk assessment module is used for calculating the overall risk of the candidate knowledge nodes based on a topology attribute vector and the scene embedding vector; the dynamic shielding module is used for shielding the candidate knowledge nodes with a counterfactual risk difference exceeding a risk threshold to obtain unshielded candidate knowledge nodes; and the recommendation output module is used for sorting the unshielded candidate knowledge nodes according to the overall risk from low to high and outputting the unshielded candidate knowledge nodes. The application can realize knowledge retrieval and recommendation which conforms to the operation law of the power grid and can avoid high-risk operations depending on the scene.

The invention relates to the technical field of knowledge base management, in particular to a knowledge base management system based on a large model, which comprises a data acquisition module, a data processing module, a knowledge base construction module and a verification module. According to the method, the text data is continuously scanned to remove repeated content and avoid word segmentation errors, the source data in the social security field is classified to collect the unstructured data in the source data to perform data conversion, namely, the text in the unstructured data is processed to identify entities and concepts in the text, and the data conversion efficiency is improved. And identifying and recording the relationship between entities, improving the availability and query efficiency of data, verifying the accuracy of word segmentation processing by combining feedback data of a user, automatically identifying whether a wrong word segmentation result appears or not by recording query data of the user, and further adjusting a word segmentation processing flow and model training parameters. The social security service system is effectively managed.

The application relates to the technical field of data interaction, and discloses a medical teaching training business problem solving method and system based on a knowledge base management system. The method comprises the following steps: collecting multi-source heterogeneous data and cleaning, constructing a knowledge graph containing problem-regulation-solution association based on a BERT model and a graph database, monitoring policies and business indexes in real time to trigger dynamic updating of the graph, generating an individualized training scheme in combination with student characteristics, monitoring a teaching process through multi-modal data and dynamically adjusting, and constructing a multi-dimensional index system to optimize the knowledge graph. The system comprises data access and cleaning, knowledge graph construction, dynamic updating, individualized scheme generation, intelligent monitoring and effect evaluation modules. The application solves the problems of special population teaching adaptation, real-time policy response and business process optimization, realizes a closed loop of 'data collection-knowledge construction-application verification' through the knowledge graph and AI algorithms, improves teaching quality and efficiency, and reduces training cost and compliance risk.

The invention relates to the technical field of knowledge base management, in particular to a knowledge base management system based on NLP and machine learning, and the system comprises a knowledge collection module which is used for receiving original knowledge data, executing text preprocessing, and generating preprocessed knowledge data; the knowledge processing and classification module is used for receiving the preprocessed knowledge data, executing text vectorization and classification and generating classified knowledge data; the knowledge storage and index construction module is used for storing the classified knowledge data and constructing a knowledge index based on the classified knowledge data; and the knowledge updating and maintaining module is used for screening the original knowledge data stored in the historical time period based on the search word input by the user and the historical search frequency, determining the optimal original knowledge data and dynamically adjusting the knowledge index and recommendation strategy.

This invention relates to the field of knowledge base management technology, and more particularly to a knowledge base management system based on NLP and machine learning. The system includes: a knowledge acquisition module for receiving raw knowledge data and performing text preprocessing to generate preprocessed knowledge data; a knowledge processing and classification module for receiving preprocessed knowledge data, performing text vectorization and classification to generate categorized knowledge data; a knowledge storage and index building module for storing categorized knowledge data and building a knowledge index based on the categorized knowledge data; and a knowledge update and maintenance module for filtering raw knowledge data stored within a historical time period based on user-input search terms and their historical search counts, determining the optimal raw knowledge data, and dynamically adjusting the knowledge index and recommendation strategy.

The invention relates to the technical field of customer service robots, and provides an intelligent customer service robot dialogue method and a knowledge base management system thereof.The intelligent customer service robot dialogue method comprises the steps that user intention recognition and information collection are achieved through a multi-round dialogue guiding module, and the module extracts keywords and analyzes sentence pattern structures through a natural language processing technology; if the intention is fuzzy, a question chasing mechanism is triggered to narrow the answering range, a standard answer is retrieved from a structured knowledge base through a knowledge base matching module on the basis of an intention recognition result, and the knowledge base comprises an FAQ base, a scene base and a case base and supports multi-mode output of texts, pictures, videos and the like. The intention of a user is accurately recognized through natural language processing and a questioning mechanism, and information collection is accelerated through an interactive menu and a form. A multi-modal knowledge base is combined with BERT semantic retrieval to improve the answer matching degree, and language style adaptation scenes are dynamically switched. The fuzzy matching algorithm judges the problem solving condition, and the process is automatically switched or restarted when the problem is not solved.

The invention particularly relates to a knowledge base management system configuration method. According to the knowledge base management system configuration method, a relational database is included, the knowledge base management system is deployed based on the xwiki technology, and services are provided for the outside or the inside; a user accesses a knowledge base management system website through a web, and uses related business functions including knowledge base management, document management and cooperative office; if the service is abnormal, checking related service state information of the xwiki technology; and realizing an automatic backup recovery function by utilizing a pgdump tool on the basis of a postgresql database. According to the knowledge base management system configuration method, centralized management and storage of internal knowledge are realized, knowledge sharing is realized, team cooperation efficiency is improved, communication cost is reduced, data security is guaranteed, and the method is suitable for popularization and application.

The invention relates to the technical field of vehicle-mounted intelligent cabins, and discloses an RAG-based vehicle function knowledge base management system and method for vehicle-mounted desktop generation. The system comprises a vehicle function knowledge base, a vehicle-mounted HMI design specification knowledge base and a user behavior habit knowledge base. The dynamic updating module is used for triggering a retrieval instruction according to the difference between the new user behavior characteristics and the historical portrait; and the retrieval output module is used for responding to an instruction, constructing a composite query based on behavior characteristics, jointly retrieving the three knowledge bases, and outputting a corresponding function definition set, an interaction specification constraint and a related user behavior mode so as to drive a large model to generate or update a vehicle-mounted desktop application. According to the method, personalized, precise and compliant generation of the vehicle-mounted desktop application is realized through behavior driving and multi-source knowledge fusion retrieval.

The invention relates to the technical field of computers, discloses a production command knowledge base management system and method based on a graph database, and aims to solve the problems of data islands, low multi-dimensional association query efficiency, difficulty in mining implicit knowledge, difficulty in tracing fault root causes and the like caused by adoption of a relational database in the prior art. The method comprises the following steps: constructing a production knowledge graph ontology model, and defining entity nodes such as equipment, personnel, materials, process and faults and relation types such as'operation ', 'cause', 'solution 'and the like; data are collected from heterogeneous data sources such as a manufacturing execution system, an enterprise resource planning system, a sensor network and an unstructured log, and are cleaned, converted and subjected to entity alignment. According to the scheme, global correlation modeling of production total elements is achieved, the complex query response speed and the fault diagnosis accuracy are remarkably improved, and dynamic evolution of a knowledge base and intelligent decision assistance are supported.

The invention provides a power grid fault processing knowledge base management system, and relates to the technical field of power grid fault processing, and the system comprises a data storage module which is used for obtaining and storing related knowledge data of the power grid industry; the knowledge graph construction module is used for constructing a power grid knowledge graph based on the related knowledge data of the power grid industry; the query retrieval module comprises a statement generation unit and a scheme retrieval unit; the statement generation unit is used for generating a graph query statement based on a power grid fault problem proposed by a user; and the scheme retrieval unit is used for retrieving a first power grid fault handling scheme from the knowledge graph based on the graph query statement. According to the system, the power grid knowledge graph is constructed, and the query retrieval module is trained through the content in the power grid knowledge graph, so that the system can quickly and accurately retrieve the corresponding power grid fault handling scheme through the power grid fault problem proposed by the user.

The invention relates to the technical field of distributed computing, in particular to an intelligent iterative knowledge base management system and method for on-site technical services, and the system comprises an edge layer which is used for collecting multi-modal data of on-site equipment in the operation process; the data acquisition layer is used for collecting multi-modal data and preprocessing the multi-modal data to obtain preprocessed multi-modal data; the distributed storage layer is used for carrying out distributed storage and deduplication storage on the preprocessed multi-modal data; the intelligent analysis layer is used for processing the preprocessed multi-modal data and constructing a technical service iteration knowledge graph; performing causal reasoning on the technical service iteration knowledge graph, and updating a pre-constructed technical iteration tree; the application service layer is used for providing field technical services for technicians according to the technical service iteration knowledge graph and the technical iteration tree, and the problems that multi-modal data fusion is low in efficiency, technical iteration manual dependence is high, knowledge and operation collaboration is poor and the like can be solved.

The present invention discloses a knowledge base management system and an enhancement method, belonging to the field of data processing technology, which specifically includes: obtaining user query information containing multiple semantic elements, and determining its IT service scenario based on the semantic elements and a pre-built IT service knowledge graph; dividing the query information into high-priority and low-priority semantic information areas according to the knowledge base dimension; quickly locating core knowledge based on the high-priority semantic information area, and improving the search results in combination with the low-priority semantic information area; triggering a multi-semantic query if a semantic element has multiple semantics; the present invention effectively improves the accuracy and efficiency of IT service knowledge retrieval and semantic understanding, and enhances the application value of the knowledge base.

The present invention relates to the technical field of express business management, and discloses a method and system for solving express business problems based on a knowledge base management system. The method first obtains the package form and semantic features, obtains a graph node state matrix through structured analysis, generates an abnormal marking matrix, establishes a mapping relationship, and then obtains multi-level calibration parameters, constructs a cross-modal mapping function cluster to obtain a package feature matrix, and then designs a knowledge base retrieval and sorting mechanism to generate a knowledge recommendation list. Finally, a solution is generated based on the list and fed back to the knowledge base. The method significantly improves the accuracy and efficiency of express business processing through multimodal data processing and the use of a knowledge base, enhances the practicality and adaptability of the knowledge base, and provides strong support for the intelligent development of express business.

This invention discloses a service knowledge base management system and method based on a large knowledge model, specifically relating to the field of knowledge base management technology. It involves real-time monitoring and preprocessing of the knowledge base system's operational status data, using decision tree algorithms to extract features and identify key performance indicators, comprehensively analyzing abnormal changes and fluctuations in the knowledge base's hit rate and update frequency, accurately assessing the system's operational stability, and classifying the system state based on the assessment results. When the system is unstable, it monitors the performance and response effectiveness of the large knowledge model, using fuzzy logic to quantify its impact on user experience, thereby taking targeted optimization management measures. Through intelligent and data-driven methods, it improves the operational stability and response accuracy of the knowledge base system, optimizes the user experience, and enhances the overall system efficiency and reliability.

The invention provides an electric power think tank knowledge base management system, and relates to the technical field of document retrieval, and the system comprises a document storage module which is used for storing electric power document data; the vector calculation module is used for calculating a document vector of each power document in the power document data; the query retrieval module is used for acquiring similarity between a problem vector of a document query problem and a document vector of each power document; and retrieving the power document corresponding to the document vector when the similarity with the problem vector is the highest from the document storage module, and outputting the power document. Document vectors of all power documents are obtained through the vector calculation module, document query problems are received through the query and retrieval module, and the query and retrieval module is trained based on a training data set, so that the power documents can be retrieved from the document storage module according to similarity between problem vectors and text vectors during query and retrieval; and the efficiency and the accuracy during power document retrieval are improved.

The present invention relates to the field of knowledge base management technology, and in particular to a knowledge base management system based on a large model, the system comprising a data acquisition module, a data processing module, a knowledge base construction module, and a verification module. The present invention continuously scans text data to remove duplicate content and avoid word segmentation errors, classifies source data in the social security field to collect unstructured data therein for data conversion, that is, by processing the text in the unstructured data, identifying entities and concepts in the text, and identifying and recording the relationships between entities, thereby improving data availability and query efficiency, verifying the accuracy of word segmentation processing by combining user feedback data, and automatically identifying whether erroneous word segmentation results occur by recording user query data, thereby adjusting the word segmentation processing process and model training parameters to achieve effective management of the social security service system.

The invention discloses a multi-type knowledge base management system, which belongs to the technical field of artificial intelligence and database management, and comprises a query interface module, a retrieval execution module, an adaptive optimization module and a service interface module, the retrieval execution module executes multi-modal retrieval according to the matrix and provides knowledge service in an AI friendly format through the service interface module, and the self-adaptive optimization module performs closed-loop automatic updating on a retrieval Prompt template and a retrieval strategy by utilizing downstream application feedback, so that unified management, collaborative calling and intelligent self-adaption of multiple types of knowledge are realized.