203 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 construction method and device of a multi-component data agent, and the construction method specifically comprises the following steps: obtaining sample data, and constructing a vector knowledge base; extracting a knowledge service flow according to the sample data, determining an ontology through knowledge representation, and forming a knowledge graph; training an initial language model based on the vector knowledge base, and giving a data processing model; and performing modularization arrangement and linking on the knowledge graph and the data processing model in combination with a logic tool chain and a thinking graph of the data intelligent agent, and constructing to obtain the multi-component data intelligent agent. According to the method, the knowledge graph is fused to construct the business rule engine, training data support is provided, the thinking chain process is modeled into the thinking graph of a graph structure, and the data processing model and the knowledge graph associated with the workflow node are executed, so that the accuracy of result reasoning of the data agent is enhanced, and the knowledge boundary is expanded; and particularly for financial auditing data, key information can be better extracted, and the working efficiency of power grid auditing personnel is improved.

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 relates to an intelligent recommendation method and device based on a knowledge graph and an intelligent recommendation system. The method comprises the following steps: acquiring a user query input by a user in a current session; determining a knowledge base corresponding to a business domain involved in the current session according to the user query; wherein the knowledge base comprises graph knowledge constructed by utilizing multi-source heterogeneous industry material data according to business requirements; determining a matched prompt word template in the current session according to the business domain involved in the current session and filling the prompt word; performing retrieval in the knowledge base to obtain context information; generating answers according to the context information and a user query input large language model, and generating recommended contents according to the answers and a prompt word template; according to the technical scheme, the real-time performance and accuracy of intelligent recommendation based on the knowledge graph are improved, the diversity and individuation degree of recommendation results are improved, and the knowledge service requirements of users are met.

The present application relates to a digital base fusion system and electronic equipment. The system includes: a data source access module, which is used to obtain raw data from design tools and data sources in different fields; a data abstraction module, which is used to manage raw data and provide a unified data access interface for upper-level modules; a semantic modeling module, which is used to build a unified semantic model; a semantic alignment module, which is used to perform semantic analysis and matching on raw data from different fields; a data fusion module, which is used to fuse semantically aligned data of corresponding types based on different fusion methods to build a unified data view; a knowledge graph construction module, which is used to build a knowledge graph based on the semantic model and the fused data; an application service module, which is used to provide data services and knowledge services for upper-level applications. The present application solves the problem that the existing digital base architecture lacks a unified semantic conversion and expression mechanism, resulting in difficulties in cross-domain data integration.

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 relates to the technical field of knowledge base construction, in particular to a knowledge service system construction method, which comprises a knowledge acquisition step for collecting knowledge data from knowledge sources of multiple fields; the preprocessing step is used for preprocessing the knowledge data; the classification step is used for classifying the obtained knowledge data; the similarity calculation step is used for calculating the similarity between different categories of knowledge bases; the first judgment step is used for judging whether the similarity is greater than a first threshold value or not; the association step is used for establishing association between the knowledge according to the similarity; the second judgment step is used for judging whether the similarity is greater than a second threshold value or not; the labeling step is used for constructing a new upper label; a label directory generation step for establishing a label directory; a query demand acquisition step for acquiring a knowledge retrieval demand of a user and generating a query request; the knowledge retrieval step is used for conducting knowledge recommendation according to the query request. The method has the effect of improving the searching efficiency.

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 provides an equipment operation manual vector knowledge base construction method. According to the method, heterogeneous multi-modal data such as texts, images, videos and three-dimensional models related to equipment are collected, semantic vector coding is conducted on the multi-modal data through a large pre-training model, the multi-modal data are fused into a unified vector space, and vector representation of equipment knowledge is constructed. An efficient index is established based on vector representation, and intelligent retrieval and association services of a semantic level are supported. And an interpretable vector coding technology is also introduced, so that the semantic interpretability of the vector is endowed, and a visual interface is provided for analyzing a vector distribution mode. And continuous expansion and optimization of the knowledge base are realized through active learning and online learning strategies. According to the method, heterogeneous data integration, intelligent semantic service, interpretability enhancement and knowledge automatic updating are realized, intelligent knowledge service support is provided for the fields of equipment operation and maintenance and the like, and the method has important application value.

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 discloses a knowledge service method combining a vector database and a graph retrieval technology. Comprising the following steps; the method comprises the following steps: S1, collecting internal data and external data in a specific field; s2, performing fine adjustment on the open source large language model through industry corpora in a specific field or starting to train from zero; s3, storing the vectorized data information in a vector database, and storing the knowledge network in a graph database; s4, establishing a graph-rag system which is used for carrying out more comprehensive expansion on questions of the user; s5, automatically matching nodes and edges in the knowledge network according to the extracted keywords; s6, fusing a vector result from the vector database and the knowledge network in the graph database; s7, updating and optimizing at regular intervals; according to the method, the efficiency and accuracy of user information retrieval are improved, the problem of information blind areas is solved, and the requirement of the user for quickly and efficiently obtaining professional knowledge is met.

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 provides a knowledge segmentation retrieval system based on nltk, and belongs to the technical field of text segmentation and retrieval, and the system comprises a knowledge uploading and segmenting module which is used for receiving and analyzing docx, pdf and txt files, segmenting the files into knowledge segments, and establishing an index; the knowledge retrieval module is used for receiving a query request of a user, quickly positioning the knowledge fragment with the highest similarity through the constructed index, and returning a retrieval result; the knowledge slice paragraph query module is used for providing a paragraph content query service after segmentation and carrying out sorting and returning according to paragraph serial numbers; and the knowledge deleting module is used for deleting a single knowledge file or the whole knowledge base and ensuring the consistency and integrity of the data. According to the method, accurate segmentation and efficient retrieval of long texts in the knowledge base can be realized, the knowledge management efficiency and quality are greatly improved, and convenient and accurate knowledge services are provided for users.

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 invention provides a medical subject knowledge service method and device, electronic equipment and a medium, and the method comprises the steps: obtaining medical literatures, and constructing a medical subject knowledge base corresponding to each subject field based on the medical literatures; obtaining a query problem input by a user, and pre-judging the query problem to determine a subject field and a query mode to which the query problem belongs; performing medical subject knowledge base query and / or medical subject big language model interaction corresponding to the subject field to which the query problem belongs based on the query mode to obtain a result of the query problem; if a second feedback result is obtained, correlation evaluation scoring is carried out on the second feedback result, and if the scoring result meets a second preset condition, a third feedback result is obtained based on the medical subject large language model, and secondary correlation evaluation scoring is carried out on the third feedback result; and finally, feeding back the second feedback result or the third feedback result meeting the requirement to the user. According to the invention, the efficiency and accuracy of acquiring the related knowledge of the medical subject are improved.

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 invention provides an AI-based electric power engineering archive knowledge service method and system in the technical field of electric power engineering archive management. The method comprises the following steps: S1, obtaining a historical archive text to construct a data set; s2, training the archive knowledge extraction model based on the data set; mining an archiving rule from historical archiving information collected from the data set through a big data technology; s3, acquiring a to-be-copied electric power engineering archive file, and performing copy identification; s4, identifying an electric power project file text from the electric power project file; s5, inputting the electric power engineering file text into the file knowledge extraction model to obtain file knowledge so as to construct a file knowledge graph; s6, extracting archiving information from the electric power engineering archive file, generating an archiving reminding notification based on the archiving information and an archiving rule, and executing archiving operation; and S7, recording the archiving characteristics in the archiving process to carry out compliance check. The method has the advantage that the quality and efficiency of electric power engineering file management are greatly improved.

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.