112 results about "Knowledge services" patented technology

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 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 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 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 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 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 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 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 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 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.

The invention discloses a natural resource knowledge service method based on a large language model. The method comprises the following steps: constructing a natural resource business knowledge base; performing vectorization processing on the constructed natural resource business knowledge base to obtain a vectorized natural resource business knowledge base; converting the vectorized natural resource business knowledge base into a natural resource business knowledge graph; training a ChatGLM large language model based on the vectorized natural resource business knowledge base and the natural resource business knowledge graph to obtain a natural resource knowledge question and answer model; carrying out vectorization processing on the input question and then inputting the question into the natural resource knowledge question and answer model; and the natural resource knowledge question and answer model outputs answers. According to the method, the defects of the prior art in the aspects of processing unstructured data in the field of natural resources, realizing accurate intelligent question answering and auxiliary decision making are overcome.

The invention relates to the technical field of archive management, in particular to a material collection contract archive whole-process collection system based on a large model agent. The system comprises a data access layer, an intelligent processing layer, a knowledge service layer, an application layer and a security compliance layer which are in communication connection in sequence. The data access layer is used for collecting multi-source heterogeneous contract data and pushing a collection result to the intelligent processing layer; and the intelligent processing layer realizes intelligent analysis, verification, state tracking and knowledge association of contract data based on a large model agent. The objective of the invention is to provide a material collection contract archive full-process collection system based on a large model agent, and by constructing a technical architecture integrating data collection, intelligent processing, knowledge precipitation and closed-loop management, automatic and intelligent management of a full life cycle from generation to archiving of contract archives is realized.

The invention belongs to the technical field of artificial intelligence, and discloses a knowledge service management method and device fusing generative AI and enhanced retrieval. Comprising the steps of constructing a knowledge base for multi-source heterogeneous data fusion, deploying a dynamic task planning engine, executing a whole-process service, establishing an evaluation and feedback closed loop and the like. Wherein the whole-process service covers AI knowledge questions and answers, AI enhanced retrieval, AI intelligent research and reading, AI auxiliary creation and intelligent agent service, and through intention recognition, mixed retrieval, RAG enhancement, cue word engineering, Deep Research and other technologies, the whole-process run-through from accurate knowledge acquisition and deep content understanding to generative creation is realized. The problems that in the prior art, knowledge obtaining efficiency is low, literature processing intellectualization is insufficient, and scientific research processes are split are solved, a credible, controllable, processized and intellectualized closed-loop knowledge service system is constructed, the efficiency and innovation ability of scientific research work are remarkably improved, and the system is suitable for various academic research and scientific research management scenes.

The invention provides a hydroelectric equipment knowledge graph retrieval enhancement method and device based on multi-modal embedding, and belongs to the technical field of intelligent perception and multi-modal semantic understanding of water conservancy and hydropower engineering. The method comprises the following steps: on the basis of related documents and pictures of hydroelectric equipment, constructing a multi-modal knowledge graph by utilizing a large language model; performing vectorization representation on pictures and text information in the multi-modal knowledge graph, and mapping the pictures and the text information to a unified semantic space to generate a vector database used for retrieving the multi-modal knowledge graph; and the vector database is utilized to retrieve the multi-modal knowledge graph. According to the method, deep fusion and semantic alignment of multi-source heterogeneous data such as images and texts can be realized, the method can be widely applied to fields such as hydropower station electromechanical equipment maintenance, hydraulic structure safety inspection and scheduling operation and maintenance knowledge management, and the equipment identification precision, the retrieval response speed and the knowledge service intelligence level can be remarkably improved.

A method by a computing system implementing a service level agreement (SLA) monitoring client to determine whether a SLA fulfillment status reported by a SLA monitoring agent is valid. The method includes verifying a proof of SLA fulfillment status based on manipulation detection codes of measurements, a SLA fulfillment status, and a verification key, determining whether the measurements are valid based on whether the distributed ledger includes measurement attestations having manipulation detection codes matching the manipulation detection codes of the measurements, and determining that the SLA fulfillment status is valid in response to successfully verifying the proof of SLA fulfillment status and determining that the measurements are valid.

The invention provides a low-voltage business expansion auxiliary decision-making system and method based on low-voltage transparency, and relates to the field of power system distribution network low-voltage operation and maintenance management. According to the invention, six modules of data access, visual management, abnormity early warning, deep mining, image identification and knowledge service are integrated, metering automation, GIS, a marketing system and low-voltage terminal multi-source data are fused, dynamic monitoring of equipment installation coverage rate and online rate is realized, and data abnormity is identified in real time through Z-score and a sliding window method. And a three-phase unbalance degree and low-voltage quantitative model is adopted to diagnose an operation problem, and in combination with LSTM load prediction, business expansion access evaluation is supported. ResNet-50 multi-mode image recognition, OCR and a knowledge graph are introduced, and automatic hidden danger recognition and operation and maintenance knowledge precipitation are achieved. The system is deployed on a cloud platform, has high security and expandability, and significantly improves the observability, operation and maintenance efficiency and decision intelligence level of the low-voltage power distribution network.

The application relates to a medical field knowledge fusion method based on label and content hierarchical fusion, and belongs to the technical field of knowledge fusion and artificial intelligence. Medical knowledge of different knowledge graphs is fused to construct a medical field knowledge base and provide large-scale medical industry knowledge services. The method comprises three steps of defining a meta label of an entity in a medical knowledge graph, data label alignment, and label content fusion. The method has the following characteristics: firstly, in the data label alignment, a data label alignment method based on integration of string measurement and semantic measurement is designed, and data label alignment is performed by using string features and semantic features. Secondly, in the label content fusion, a joint mechanism of content aggregation verification and unstructured knowledge generation is proposed, which aims to extract common knowledge of different granularities in different knowledge graphs, verify contradictory knowledge, and convert common triple knowledge into unstructured sentences to construct a medical knowledge base.

The application provides an agricultural knowledge service method and system, the method comprises the following steps: crawling an agricultural information data source to obtain heterogeneous knowledge information of a target agricultural knowledge user; inputting the heterogeneous knowledge information into an agricultural knowledge graph model to obtain an interest prediction result output by the agricultural knowledge graph model; and pushing knowledge service content matched with the interest prediction result to the target agricultural knowledge user. The agricultural knowledge service method and system provided by the application realize automatic identification and extraction of user preferences through a multi-layer neural network, and the user preference prediction is more accurate. In particular for new users who have not interacted, the potential preferences of the new users can be represented through users having social relationships, effectively avoiding the problem of new user cold start, and greatly improving the pertinence and timeliness of agricultural knowledge service.

The invention discloses a maternal and infant knowledge service method and device, computing equipment, a storage medium and a program product. The method comprises the steps of obtaining query information carrying maternal and infant knowledge requested to be queried by a user; based on the query information, calling a preset large model to generate a query result corresponding to the query information, the preset large model being obtained by pre-training based on question and answer data of multiple classified maternal and infant knowledge; and outputting a query result. Through the preset large model trained by the maternal and infant field data, the understanding and generation quality of maternal and infant knowledge problems is improved; according to the method, multi-classification knowledge coverage is achieved, the adaptability to different mom and infant subdivision scenes (such as physical examination, antenatal training and safety) is enhanced, data can be optimized according to classes when the model is trained or optimized due to multi-classification, and the efficiency is high.

The invention discloses an intelligent question and answer service platform based on a cigarette sweetness knowledge graph, and relates to the technical field of tobacco industry, and the platform comprises a knowledge graph module which is used for storing the cigarette sweetness knowledge graph and achieving the dynamic updating of knowledge, and the knowledge graph comprises the incidence relation between cigarette sweetness entities and entities; the mixed matching module comprises a regular expression matching unit and a vector similarity matching unit and is used for processing user query; the question and answer processing module is used for receiving queries, matching knowledge and generating natural language answers; and the personalized service module is used for providing personalized recommendation and query optimization according to the user portrait. According to the method, professional knowledge query in a natural language form is realized, the problems of low efficiency and poor interactivity of existing cigarette sweet knowledge retrieval are solved, and efficient and accurate knowledge service and decision support are provided for tobacco production personnel. And meanwhile, dynamic updating and personalized recommendation of knowledge are realized, and the practicability and adaptability of the platform are improved.

1. Name of the product in this design: Interactive graphical user interface for mining knowledge service platform of electronic equipment. 2. Purpose of this design product: for use in an electronic device. 3. The key design point of this design product lies in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: Main view of Design 1. 5. Designate Design 1 as the base design. 6. Other situations that require explanation: This graphical user interface is used for interaction with the mining knowledge service platform. The main views from Design 1 to Design 4 represent the interface of the mining knowledge service platform, where users can implement corresponding product functions by operating the relevant controls.

A system and method for protecting user data using a key escrow service. The key escrow service may be hosted by a service provider to integrate Identity Access Management (IAM) solutions, such as Single-Sign-On (SSO) and / or System for Cross-domain Identity Management (SCIM), with a zero-knowledge service, such as a password manager or other service handling sensitive user data. In examples, secure enclave technology may be used to allow the service provider to host and manage the key escrow service without being able to access any cryptographic key used and / or stored within a secure enclave. Accordingly, in some aspects, the service provider may have the ability to store users' secret keys for SSO and sharing keys for SCIM in a trusted, secure storage location without breaking the zero-knowledge principles of the infrastructure.

This invention proposes a method and system for semantic enhancement of data assets based on knowledge graphs and large-scale models. The method includes: performing lexical segmentation and functional classification on the natural language query input by the user; generating context-aware word-level semantic representations using a context-aware semantic encoder and aggregating them to obtain query-level semantic representations; combining the functional classification results with the query semantics, constructing a structural path generation request in the knowledge graph; performing path search and scoring to filter target paths; when a path is missing or the score is insufficient, locating semantically weak links and generating structural completion suggestions; finally, generating a response based on valid paths or completion suggestions, and writing the suggestions into the candidate enhancement area of ​​the knowledge graph when conditions are met. This invention improves the semantic understanding accuracy and graph interaction capabilities of natural language queries in data asset management scenarios, supporting interpretable and evolvable knowledge services.