146 results about "Knowledge services" patented technology

The invention relates to a brilliance large-scale model culture knowledge generation and retrieval method combined with a knowledge graph. The method comprises the steps that entity extraction, relation modeling and dynamic completion processing are carried out according to multi-modal culture data, a culture knowledge graph is constructed in combination with a fuzzy time reasoning algorithm and a cross-modal alignment mechanism, and the multi-modal culture data comprises an unstructured culture text, image data and space-time metadata; the space-time metadata comprises text space-time metadata and image moment metadata; performing semantic alignment processing by combining a large model through a user query statement and a culture knowledge graph to obtain joint representation of cross-modal semantic alignment; and performing multi-modal retrieval-generation joint optimization based on the joint representation to obtain cultural knowledge description and associated multi-modal content. According to the method, through multi-modal data fusion, dynamic knowledge completion and fuzzy time reasoning, culture knowledge description can be accurately generated, associated multi-modal content can be retrieved, and the accuracy and the intelligent level of culture knowledge service are improved.

The invention discloses a knowledge exploration method and system based on a generative thinking chain and a feedback mechanism, and the method comprises the steps: receiving a multi-modal query inputted by a user, and carrying out the intention analysis to recognize a core demand; preprocessing the multi-modal query, extracting key information, and decomposing a complex problem into a plurality of sub-problems or sub-tasks; dynamically constructing a hierarchical reasoning path based on the generative thinking chain, and marking a logic basis for each step of reasoning path; reasoning path priority is optimized through dynamic weight distribution, a reasoning strategy is dynamically adjusted on line in combination with a meta-reinforcement learning framework, and a reasoning path is optimized; verifying the reasoning path by using a causal reasoning analysis tool, and generating an anti-fact path to correct error nodes; and outputting a structured text and a visual reasoning process, and optimizing model parameters in real time based on multi-user feedback aggregation of the game theory. According to the method, the problems of intelligent query and reasoning in a complex scene can be effectively solved, and the accuracy, real-time performance and credibility of knowledge service are realized.

The invention discloses a dynamic intention recognition and GraphRAG fusion method and system for open domain questions and answers, and relates to the technical field of intelligent and natural language processing. The method comprises the following steps: constructing and dynamically updating a heterogeneous knowledge graph; performing dual-stage intention recognition on user query; subtasks are disassembled based on an intention result, and cooperative execution is carried out through multiple agents; service standardization integration is realized by means of a model context protocol; and closed-loop optimization is carried out in combination with user feedback. The system comprises an image knowledge base, an intention recognition module, an agent collaboration module, an MCP service integration module and a feedback optimization module. The system is a novel open domain question-answering system integrating structured knowledge modeling, dynamic intention understanding, intelligent collaborative reasoning and standardized service interaction, and through fusion of structured knowledge modeling and intelligent collaborative reasoning, question-answering accuracy and complex intention understanding ability are improved, system adaptability and efficiency are enhanced, multi-system collaboration is promoted, and the system has a wide application prospect. The method is suitable for scenes such as knowledge services and intelligent assistants.

The invention provides a knowledge base question-answering system optimization method and device based on hybrid fine tuning and multi-dimensional evaluation and a readable storage medium thereof, and provides the following scheme: constructing a hybrid progressive fine tuning framework, fusing low rank adaptation (LoRA) and direct preference optimization (DPO), and realizing domain knowledge migration through hierarchical dynamic parameter configuration; establishing a logic-semantic-knowledge three-dimensional quantitative evaluation system, and forming closed-loop optimization by using dynamic weight fusion and a visual decision system; and designing a multi-domain prompt template library with layered parameter freezing, sparse constraint and attention driving, and realizing model lightweight and cross-domain logic constraint. According to the method, the adaptive bottleneck of a general model and domain characteristics is broken through, the small sample training efficiency and the generated content compliance are improved, the computing resource consumption is reduced, an efficient and reliable knowledge service base is provided for professional scenes such as laws, medical treatment and finance, and the technical advantages of specialization, light weight and interpretability are achieved.

The invention discloses intelligent knowledge service electronic equipment for information retrieval, and the equipment comprises a data management layer which is responsible for providing original data for a cognitive calculation layer, and carrying out the closed-loop optimization through continuously monitoring the feedback of a man-machine interaction layer; the cognitive calculation layer is responsible for converting original data into a semantic tag system and a dynamic knowledge graph, applying BERT + GNN hybrid analysis, BERT processing text context and GNN analysis entity relationship in the knowledge graph, and dynamically adjusting a reasoning path according to user field preference by combining an SWRL rule engine and reinforcement learning; the service arrangement layer is responsible for extracting data from the multi-modal data pool, solidifying and arranging a complex query stream to perform logic decoupling and efficient multiplexing, and providing a visual interface to support non-technical personnel to configure a new scene; and the man-machine interaction layer is used for constructing a natural interaction bridge through the structured answers and the visual maps output by the service arrangement layer, carrying out personalized interface adaptation based on historical dialogues, and establishing a user feedback closed loop.

The invention discloses a preschool education field knowledge base construction method fusing a knowledge graph and a large language model, and relates to the technical field of preschool education method optimization. Multi-channel collection of preschool education data and cleaning preprocessing; utilizing a customized model to extract entities and relationships, and constructing a structured knowledge graph; performing fine tuning on the big language model in the preschool education field; fusing atlas and model knowledge through a gating mechanism, and performing dual verification; establishing a monthly updating mechanism to realize incremental learning; in addition, personalized knowledge recommendation is realized based on a user portrait, interactive questions and answers are optimized through combination of retrieval and a model, and data security is guaranteed by adopting anonymization and authority control. Through multi-source data integration and intelligent technology fusion, an accurate and dynamic preschool education knowledge base is constructed, requirements of children are more accurately understood, content fitting cognition is generated, personalized learning recommendation is realized, interaction experience and knowledge service quality are improved, data security is guaranteed, and digital upgrading of the preschool education field is promoted.

The invention discloses an RAG intelligent retrieval question-answering system and method based on enhanced metadata, and relates to the technical field of information processing and intelligent retrieval, multi-source heterogeneous knowledge data is preprocessed to obtain unified knowledge data, and structured metadata is extracted from the unified knowledge data based on different text forms; vectorizing a document text in the structured metadata by combining with embedding of the knowledge graph to obtain document representation, and outputting the document representation, the structured metadata and the enhanced keyword set as an enhanced metadata object; labeling a display relationship between different enhanced metadata objects, and constructing to obtain a knowledge database; according to the intelligent knowledge service system and method, restrictive conditions and question intentions are extracted from user questions, mixed retrieval is performed from a knowledge database based on the restrictive conditions and the question intentions, a candidate literature semantic set is output, then structured statistical visualization reports and structured answers are output, and accurate, explainable and multifunctional intelligent knowledge services are achieved.

The invention belongs to the technical field of power equipment operation inspection auxiliary decision making, and particularly relates to a power operation inspection knowledge service method and device, equipment and a medium. The method comprises the following steps: analyzing semantics of query input of a user by utilizing a large semantic model, and determining a corresponding target sub-knowledge base in combination with an intention classification sample library and an intention set; performing sentence segmentation on the document of the target sub-knowledge base, generating document fragments containing continuous sentences through context supplementation, and enabling semantics of the document fragments to be overlapped; calculating a keyword correlation score of the query word and the document fragment; generating a text vector through a semantic coding model, and calculating a semantic correlation score of the query input and the document fragments; fusing the keyword correlation score and the semantic correlation score, and outputting each related document fragment according to a comprehensive score sequence; and inputting query input of a user and related document fragments into the large semantic model, and generating a structured answer in combination with the logic in the operation and inspection field of the power equipment. And the electric power operation and maintenance knowledge service with high accuracy and strong generalization is realized.

The invention discloses an industry knowledge graph automatic construction method oriented to multi-source heterogeneous data, and relates to the technical field of knowledge engineering. Structured, semi-structured, unstructured and distributed data are supported, and high-concurrency data are cached through Kafka; preprocessing and standardizing, and executing cleaning, field unification, text conversion and format conversion; a pre-training model and a rule engine are adopted to cover entities and relations of multiple industries; designing a dynamic Schema, storing the dynamic Schema in a graph database, and constructing an index; evaluating and correcting from multiple dimensions; and dynamic updating and maintenance, incremental updating based on data change, and support of version management and knowledge service. According to the method, the knowledge graph is automatically constructed through multi-source heterogeneous data, the construction efficiency and quality are improved, cross-domain fusion is supported, dynamic updating is adapted, and multi-industry intelligent application is assisted.

The invention relates to the technical field of medicine and artificial intelligence, and discloses an elderly care-oriented medical and nursing combined knowledge service system construction method, which comprises the following steps of collecting sentiment expression data of the elderly, applying a nonlinear time sequence analysis and deep learning model, extracting sentiment dynamic characteristics, and obtaining sentiment expression data of the elderly; recognizing an early signal with reduced emotion regulation ability; on the basis of the obtained emotion dynamic features, a memory enhanced attention network is combined with a psychological knowledge graph, an individualized emotion cognitive interaction model of the old people is constructed, a dynamic interaction mechanism between an emotion state and a cognitive mode is revealed, and key intervention nodes are recognized; based on an emotion cognition interaction model and a key node recognition algorithm, the system can accurately position key links of mutual influence of emotion and cognition, and targeted intervention is achieved; and a dual-channel collaborative intervention strategy adjusts an emotional state and reconstructs a cognitive mode through multi-agent reinforcement learning, and breaks through an emotional cognitive vicious circle.

The invention relates to an archive credible question and answer method based on graph context retrieval and knowledge graph enhancement, and belongs to the field of computer software and artificial intelligence. According to the method, the relation between key entities and entities in a historical file is extracted by using a multi-modal large language model MLLM, and low-confidence fields are automatically identified to generate marks needing to be manually rechecked, so that the correctness of information extraction is ensured while the workload of manual rechecking is reduced, and then based on a given knowledge base, the information extraction efficiency is improved. Previous related questions and answers are retrieved according to query questions to achieve context enhancement, and finally, credible answers are generated through a large language model (LLM) in combination with extracted information in historical archives. On the premise of keeping the value of the archive voucher, the processing efficiency and the knowledge service capability are remarkably improved.

The invention discloses an accompanying dialogue system and method based on real-time environment perception and knowledge graph enhancement. The system comprises a multi-mode real-time environment perception module, a knowledge graph construction and enhancement module, a natural language understanding and dialogue management module, a personalized recommendation and narration generation module and an immersive multi-mode interaction module. The method comprises the steps of multi-modal real-time environment perception and situation data generation; performing dynamic association, query and enhanced reasoning on the knowledge graph; natural language understanding and dialogue management, personalized recommendation and narrative generation, and immersive multi-modal interaction presentation and feedback reception. According to the method and the system, the concern point of the user, namely scenery or details, can be accurately positioned, and context information required by subsequent service intelligence is provided, so that the problems of poor environment perception ability, weak interaction immersion, dull knowledge service, lack of individuation, insufficient intelligent accompanying experience and the like in the existing tourism auxiliary technology are solved.

The invention provides a dynamic knowledge graph construction method and system based on large model driving, and relates to the technical field of dynamic knowledge graph construction, and the construction method comprises the steps: collecting multi-source data, collecting new knowledge and user search data in real time, and extracting entities and relationships through preprocessing to construct a knowledge graph. And constructing a graph attention network model optimized by an annealing moth optimization algorithm, inputting new knowledge according to a preset interval to obtain a fusion strategy, fusing the data to obtain entity update data, and adjusting the data and updating the graph according to user tendency to obtain a personalized dynamic knowledge graph. According to the method, the tendency data is extracted from the user search data, personalized adjustment is performed on the knowledge graph, so that new knowledge can be accurately fused into the knowledge graph, data conflict and redundancy are avoided, higher-quality and more personalized knowledge services are provided for users, and the application value of the knowledge graph in various fields is improved.

The invention relates to a data processing method and system, in particular to a vocational education multi-source data federation treatment method and system, and belongs to the technical field of vocational education informatization and big data. Then constructing a knowledge graph in a triple form and mapping the knowledge graph to a multi-dimensional tensor space; secondly, multi-source data compatibility is analyzed and evaluated through topological features, and feature fusion maintaining topological invariants is executed; finally, knowledge reasoning and service are provided based on a quantum probability field model, the complex relation expression ability is improved through tensor representation, the heterogeneous data fusion quality is guaranteed through topology durability, the uncertainty in knowledge service is processed by introducing the quantum probability theory, and the reliability of the knowledge reasoning and service is improved. The problems of multi-source heterogeneous, complex relation, insufficient service accuracy and the like of vocational education data are effectively solved, and a comprehensive data federation governance solution is provided for the vocational education field.

The invention relates to the technical field of artificial intelligence and knowledge engineering, and provides a digital human knowledge graph dynamic iteration system and method based on user feedback. According to the method, the timeliness and automation level of knowledge updating are improved; the configuration efficiency of technical resources is optimized; a data-driven iterative verification closed loop is constructed; according to the knowledge service system, the maintainability and robustness of the system are enhanced, the system has the capabilities of tracking, querying and rollback any change, the risk of system service degradation caused by misoperation or invalid updating is greatly reduced, and the stability of the whole knowledge service system is improved.

The invention discloses a book data processing and intelligent service system based on artificial intelligence, and relates to the technical field of artificial intelligence and digital library crossing, and the technical scheme is characterized in that a multi-format document intelligent conversion and regular cleaning mechanism is adopted, a multi-level metadata extraction algorithm is combined, and a structured knowledge base is accurately constructed; vector semantic retrieval, BM25 keyword retrieval and a cross encoder reordering model are creatively fused, and high-precision context retrieval is achieved through dynamic weight configuration and locality sensitive hash de-duplication. A parallel data processing architecture supporting GPU acceleration is constructed based on a Chroma vector database, the knowledge response capability of a local large model is enhanced in combination with an RAG technology, and verifiable standardized content is generated. The system is compatible with a Linux / Windows platform and containerized deployment, has hundred million-level data throughput efficiency, can be widely applied to the fields of intelligent libraries, knowledge questions and answers and personalized recommendation, and remarkably improves the retrieval accuracy of book data and the intellectualization level of knowledge services.

The invention relates to the technical field of artificial intelligence, in particular to a question and answer method and system based on LLM fusion knowledge graph and retrieval enhancement generation. The entities which are connected with the known entities and do not appear in the local knowledge graph are marked as related entities through the graph structure connection relation, a new local knowledge graph is formed, descending sorting is carried out according to the edges and the weights in the connected components, when the weights are the same, the lexicographical order of the entity names is used as a second sorting key, and the second sorting key is used as a third sorting key; and after sorting is completed, according to the sorting sequence, until the accumulated number of the documents reaches a preset number, combining the finally obtained individual documents with the questions, and inputting the combined documents and the questions into a large language model to generate a final answer. According to the method, the accuracy and interpretability of questions and answers can be effectively improved, the illusion problem of a large language model is solved, and reliable knowledge service support is provided for a complex decision-making scene.

The invention provides a self-adaptive transformation and migration method and system for an internal website, and relates to the technical field of website migration. Comprising the following steps: constructing a hierarchical credential adaptation architecture, establishing a dynamic authority-data mapping mechanism, realizing knowledge base-data migration linkage and deploying an adaptive security protection chain. The method is used for realizing collaborative improvement of compatibility, security and knowledge service efficiency of an internal website in a credential environment through hierarchical credential adaptation, dynamic permission and data association, knowledge base linkage and self-adaptive security protection; besides, through cooperative work of the hardware driving adaptation module and the software interface conversion module, automatic identification of hardware features and interface features, precise analysis of adaptation requirements and dynamic generation of configuration files are realized. The compatibility of an internal website to different models of servers, autonomous controllable components and software interfaces in a credential environment is remarkably improved, the adaptation period is shortened, and stable operation of the system is guaranteed.

The embodiment of the invention discloses an intelligent response method and system based on a large model and a storage medium. The system comprises a user input module which is used for acquiring input information of a user; the keyword extraction module is used for extracting key information corresponding to the input information through a large model; the historical record conjoint analysis module is used for determining a plurality of dimension features of the user according to the key information and the historical record information; the permission judgment module is used for determining the knowledge base with the access permission of the user according to the permission level; the comprehensive portrait establishing module is used for generating a dynamic user portrait according to the multiple dimension features of the user; and the knowledge recommendation module is used for outputting a personalized reply of the user according to the dynamic user portrait and the knowledge base with the access authority of the user. According to the embodiment of the invention, through multi-dimensional analysis of user behaviors and historical data, an accurate user portrait is constructed, user demands are accurately matched, personalized knowledge recommendation is provided, and the knowledge service accuracy is remarkably improved.

The invention discloses an intention recognition and multi-path recall dynamic weighted fusion retrieval method and system, and the method comprises the steps: processing heterogeneous data such as PDF and pictures through a fruit industry unified document object model, and constructing a multi-type index through semantic adaptive slicing; after user query is preprocessed, intention categories and confidence coefficients are recognized through a fruit industry fine tuning model; performing keyword, vector and map retrieval in parallel, and dynamically distributing fusion weights based on intentions; performing authority, timeliness and consistency voting arbitration on conflict results; and after the answer is generated, the illusion is inhibited through entity and numerical value verification. According to the method, the problems of poor adaptation, model illusion, data islands and conflict arbitration-free of existing single retrieval are solved, the fruit industry retrieval accuracy and reliability are improved, the agricultural production risk is reduced, and the method is suitable for large-scale fruit industry knowledge service.

The present application relates to a data processing method and system, in particular to a vocational education multi-source data federal governance method and system, belonging to the field of vocational education informatization and big data technology, which first acquires and preprocesses vocational education multi-source data through network crawler and OCR technology; then constructs a knowledge graph in the form of triplets and maps it to a multi-dimensional tensor space; then evaluates the compatibility of multi-source data through topological feature analysis, and performs feature fusion that maintains topological invariants; finally, based on a quantum probability field model, knowledge reasoning and services are provided, the present application uses tensor representation to improve the expression ability of complex relationships, ensures the quality of heterogeneous data fusion through topological persistence, and introduces quantum probability theory to handle uncertainty in knowledge services, effectively solving the problems of multi-source heterogeneous vocational education data, complex relationships and insufficient service accuracy, and providing a comprehensive data federal governance solution for the vocational education field.

The invention relates to the technical field of medical health information services, in particular to a cerebral apoplexy knowledge question-answering system construction method and system based on a knowledge graph and a large language model. Natural language input of a user is analyzed through a query agent, a query intention and constraint conditions are recognized, and a structured execution plan is generated; a user state management tool is forcibly activated, a static clinical portrait and a dynamic rehabilitation log are loaded, and a personalized context is constructed; a plurality of tools such as knowledge graph query, authoritative literature retrieval and rehabilitation plan generation are scheduled, and accurate retrieval and reasoning of heterogeneous knowledge are completed; through double verification of fact consistency and clinical risks, error or high-risk suggestions are intercepted and replaced with risk early warning. The problems of'illusion 'risk, insufficient individuation, poor interpretability and the like of a traditional single model are solved to a large extent, high-credibility, individuation and traceable rehabilitation knowledge service can be provided for the stroke patient and a caregiver of the stroke patient, and rehabilitation safety and effect are guaranteed.

The invention discloses a knowledge retrieval method, device and equipment based on a model, a medium and a product, and relates to the technical field of natural language processing. The knowledge retrieval method based on the model comprises the following steps: acquiring insurance knowledge information to be queried; according to the insurance knowledge information to be inquired and a predefined association mechanism, association knowledge dimension information is determined; performing multi-dimensional similarity determination on knowledge results contained in the knowledge base according to the associative knowledge dimension information to obtain similarities of the knowledge results under different dimensions; and determining a query result according to the similarities. And determining potential associative knowledge dimension information in the insurance knowledge information to be queried based on a predefined associative mechanism, and obtaining a final query result through multi-dimensional similarity determination. According to the method, intelligent association and accurate retrieval of knowledge are achieved, the retrieval accuracy and response speed are remarkably improved, the query result better meets user requirements, and efficient and intelligent knowledge services are provided for users.

The invention discloses a decision-making method of a steel product and related equipment, and relates to the technical field of knowledge maps, and the method comprises the steps: obtaining multi-source heterogeneous data of the steel product; performing entity identification and relation extraction operation on the multi-source heterogeneous data, and constructing a customer service knowledge graph and a manufacturing and production knowledge graph; based on the customer service knowledge graph and the manufacturing production knowledge graph, generating a steel product target knowledge graph; based on the target knowledge graph of the steel product and the problem description information of the customer for the steel product, performing knowledge graph reasoning operation, and determining potential risk types and associated process nodes associated with the problem description information; and based on the potential risk type and the associated process node, generating decision suggestion information oriented to the problem description information. According to the method, professional knowledge and experience dispersed in multi-source heterogeneous data are effectively integrated, end-to-end professional knowledge service support is provided, and the service response speed and quality are improved.

The invention discloses an animal nutrition and feed course resource sharing cloud platform and a knowledge graph construction method. The method comprises the steps of obtaining feeding knowledge resource data of different animal types and constructing a feeding knowledge meta-database; performing multi-granularity entity recognition and analysis on the feeding knowledge resources in the feeding knowledge meta-database to generate four types of entity sets, constructing an entity interaction graph, performing entity relationship reasoning to obtain a triple set, and constructing a feeding resource knowledge graph by using the triple set; constructing a personalized recommendation engine, carrying out user question answering and demand knowledge recommendation through the personalized recommendation engine, and carrying out interest resource recommendation based on user use behaviors; and building an animal nutrition and feed course resource sharing cloud platform by utilizing a micro-service architecture technology based on the personalized recommendation engine, the feeding knowledge meta-database and the feeding resource knowledge graph. Therefore, accurate, real-time and multi-dimensional knowledge service and help are provided for animal husbandry practitioners or interests and amateurs.

The invention discloses a wind power fault knowledge graph construction method based on an improved event extraction technology. The method specifically comprises the steps that firstly, a wind power fault case data set is acquired and marked and divided; then, designing an improved event extraction model ACFGEE, and carrying out training and evaluation; secondly, performing deployment testing on the event extraction model after evaluation is completed; modeling a fault event ontology and importing the ontology and extracted data knowledge into a Neo4j graph database to realize knowledge storage so as to construct a wind power fault event knowledge graph; and the knowledge service comprises a knowledge query service for visually displaying the wind power fault event knowledge graph and a knowledge recommendation service for carrying out fault maintenance recommendation on the fault event based on cosine similarity. The method can be widely applied to a fault diagnosis and decision support system of a wind power plant, helps operation and maintenance personnel to quickly position problems, improves the operation efficiency and economic benefits of the wind power plant, and has been successfully applied to a certain wind power plant for fault diagnosis and decision support.

The invention discloses an AI knowledge service system and method based on a financial intelligent context protocol, and relates to the cross technical field of artificial intelligence and financial science and technology, and the system comprises a financial query understanding and routing layer, a financial document relationship modeling layer, a financial intelligent context protocol intelligent context regulation and control layer, and a financial compliance guarantee layer. Through financial field innovation of a financial intelligent context protocol (F-MCP) protocol, the application effect of AI knowledge service in a financial scene is remarkably improved; in the technical level, compared with a traditional retrieval enhancement generation (RAG) system, the financial illusion rate is reduced by 75%, and the retrieval precision is improved by 45%; in the business level, the key pain points of poor timeliness, high compliance risk and the like of financial information are effectively solved; in the engineering level, the integration complexity is reduced by 40% through modular design, and financial-level security deployment is supported; and on the application level, a technical basis is provided for large-scale deployment of financial AI application, financial science and technology innovation and industry digital transformation are promoted, and the method has remarkable technical value, commercial value and social value.

The invention relates to the technical field of medical informatization, in particular to a clinical aid decision-making optimization method, device and equipment based on guide knowledge, and the method comprises the steps: obtaining electronic medical record data from a hospital information system and a laboratory information management system communication system, data standardization is achieved through the steps of duplicate removal, missing value processing, abnormal value processing, format standardization and the like; according to authoritative knowledge such as clinical pathways, diagnostic guidelines and disease consensus provided by doctors, key feature information is extracted by utilizing a natural language processing technology, structured data is extracted by adopting a regular expression, and unstructured texts are marked by pre-training a medical word vector dictionary, performing word segmentation by a classifier and performing part-of-speech tagging. The weight is optimized based on the loss function; an initial case knowledge base is constructed, and high-quality cases are screened out according to evaluation indexes such as knowledge richness and curative effect; dividing the high-quality cases into well-known physician cases and rare disease cases through syntactic analysis according to the classification indexes; case matching is carried out by adopting selective weighted heterogeneous value distance measurement, discrete attributes adopt value difference measurement, continuous attributes adopt standardized difference square, and attribute weights are optimized by means of a genetic algorithm, so that auxiliary clinical decision and knowledge services are realized. The invention can provide a scheme which can efficiently construct a high-quality case library, automatically extract key feature information, fuse guide knowledge for classification and screening, and introduce more accurate measurement and weight optimization in matching.

The invention belongs to the technical field of enterprise knowledge management, and particularly relates to a loose coupling type knowledge management system comprising a resource layer used for collecting knowledge on departments and personal computers, including structured and unstructured data, converting the unstructured data into structured data for preliminary storage, and storing the structured data in a database; and meanwhile, an interface is designed for recording and synchronizing data. According to the system, efficient integration and sharing of knowledge are achieved, the quality and efficiency of enterprise knowledge management are remarkably improved, all kinds of knowledge are collected through the resource layer and converted into structured data to be stored, unified classification processing is conducted through the resource integration layer, dominant and implicit knowledge is stored through the resource library layer in a classified mode, employees can conveniently obtain the needed knowledge, and the enterprise knowledge management efficiency is improved. The knowledge searching time is shortened, the service layer provides multiple knowledge service functions, repeated labor and loss of knowledge are avoided, rich intangible knowledge assets are accumulated for enterprises, and the core competitiveness of the enterprises is enhanced.

The invention discloses an academic publication knowledge service intelligent management system and method based on digital twinning, and relates to the field of knowledge service and technology, and the system comprises a data storage module, a dimension weight quantification module, a weight distribution difference analysis module, an effective trigger distribution model construction module and a response priority analysis module. According to the method, the initial weight of each dimension is quantified through six dimensions including multi-dimensional intelligent retrieval, covering knowledge elements, semantic understanding and user portraits, the weight can be dynamically allocated according to user retrieval content features such as whether keywords contain limits or not, new and old attributes of the users and keyword expansion capacity, the weight is updated based on subjective operation contents of the users, and the user experience is improved. The retrieval strategy is deeply matched with the individual requirements of the user, the problem of low retrieval efficiency is greatly reduced, and the operation cost of repeatedly modifying retrieval conditions by the user is reduced.