70 results about "Knowledge processing" patented technology

The invention discloses a field event element extraction method and system based on prompt learning and knowledge completion, and the method comprises the steps: converting an extraction task into a constrained generation problem through structured prompt, achieving the stable extraction under a small number of labeled samples through the existing knowledge prior of a large language model, reducing the dependence on large-scale labeled data, and improving the extraction efficiency. And the cross-domain adaptive capacity is improved. A vectorization knowledge retrieval mechanism is introduced, related evidences are obtained from an external knowledge source, elements which are not clearly expressed in a text are complemented, the integrity of information is enhanced, and the accuracy and credibility of a result are improved through knowledge verification. And through a self-adaptive fusion mechanism of prompt and knowledge, the model can flexibly balance text context and external knowledge, and the robustness of complex context and fuzzy expression is improved. And finally, standardized and structured element data are output, a convenient interface is provided for downstream event atlas construction and analysis tasks, and the automation degree of domain knowledge processing and the system integration efficiency are improved.

The invention discloses a method and a system for automatically generating a video based on multi-agent unstructured knowledge, and relates to the technical field of video automatic generation based on knowledge processing, and through a data source weight evaluation mechanism and a content semantic similarity calculation method, repeated or contradictory knowledge fragments are automatically identified, a disputed knowledge unit list is established, and the video is automatically generated according to the disputed knowledge unit list. And analyzing the matching degree of the dispute content and the preset script by adopting a semantic vector similarity algorithm. And for the recognized dispute knowledge points, a standby knowledge replacement algorithm is applied to retrieve replacement contents with high confidence from a reliable knowledge base, a knowledge unit replacement operation is executed, and high-quality video output with dispute identification is generated, so that the content accuracy and credibility of the multi-source knowledge fusion video are effectively improved. According to the method, a whole-process quality control system from knowledge identification to video generation is established, intelligent matching of knowledge credibility evaluation and a video content presentation mode is realized, and practical deployment of the technology is restricted.

The invention discloses a multi-source feature collaborative knowledge mining and semantic association method, and belongs to the technical field of full-life-cycle knowledge processing of railway track engineering. According to the method, field-related documents are screened, an element range and a processing sequence are limited in combination with a knowledge graph, the documents are customized to generate a term candidate set, term statistical weights are calculated based on a full-life-cycle corpus, dynamic semantic vectors are generated by utilizing a field self-adaptive pre-training model, and composite concept representation is obtained through fusion of an attention mechanism. And linking the knowledge graph to construct a heterogeneous graph, mining association through a graph attention network, analyzing, querying and verifying sequential logic, and then outputting structured knowledge. According to the method, the problems of railway track engineering data islands and cross-stage semantic segmentation can be solved, low-frequency key terms are accurately recognized, the result interpretability is enhanced, applications such as design optimization and construction management and control are directly supported, and the method is adaptive to multiple engineering professions and high in practicability.

The application provides a knowledge processing method and device for power inspection defect detection, and the method comprises the following steps: obtaining an optimal path to connect a starting point entity and an ending point entity in the power equipment knowledge graph to form a Markov decision process according to the starting point entity and the ending point entity; training the Markov decision process to obtain a trained Markov decision process; an agent in the trained Markov decision process selects output edges in turn by using a random beam search strategy, and traverses to a new entity; when the agent searches for an optimal path by using the random beam search strategy, the path automatically forms a predicted explainable source. The application not only makes the power equipment knowledge graph knowledge completion explainable, but also improves the ability to understand complex environments and infer high-level causal relationships.

The application discloses a bank intelligent operation knowledge base implementation method and system based on a large language model and RAG. The method first extracts business terms from structured, semi-structured and unstructured multi-source heterogeneous multi-modal data of a bank, and then constructs a business dictionary and an ontology tree containing term similarity data. Then, the release agency weight, time effectiveness coefficient and penalty correlation degree of the regulatory provisions are quantitatively calculated to obtain an authoritative value and sort. Then, the pre-trained large language model is fine-tuned as a vector representation model using a double-constraint loss function, and the business data is vectorized and stored in a vector database. Finally, for user queries, the vector database is retrieved and combined with the regulatory provision sorting result for rearrangement, and a business response is generated after compliance verification. The method can improve the unstructured knowledge processing capability and retrieval accuracy of the bank, and realize efficient intelligent operation.

The application provides a kind of construction method of intelligent question answering system based on computer discipline knowledge graph, first constructs computer discipline ontology, then utilizes crawler technology to collect unstructured data such as electronic books and baidu encyclopedia, completes knowledge processing based on Colabeler tool, BiLSTM-CRF, BiLSTM-ATT, stores the extracted entity, relationship and other data to Neo4j, and finally establishes intelligent question answering system based on backend Flask framework and front-end React framework. First, the keywords of the question are extracted, and the template is matched. If no answer is matched, the relevance of the question is analyzed, and the question is stored in the relational database. The teacher answers, extracts the effective information of the teacher's answer using the knowledge extraction model, and supplements it to the knowledge graph to update the knowledge graph. The application has three characteristics of data structuring, storage refinement and intelligent question answering, which solves the problems of scattered and irregular computer discipline data, coarse discipline knowledge granularity and inaccurate search results.

Techniques are provided for a large language models (LLM) to reduce risks associated with potential introduction of factual inaccuracies and / or hallucinations in responses to user queries to the LLM, for example when responding to user queries pertaining to advanced scientific fields. One or more documents from a document corpus are identified to generate a response to a user query, and relevant information points for (e.g., citations to) the one or more documents are associated therewith to demonstrate accuracy of the response. Validation techniques may be provided to further ensure accuracy of the response to the user query.

The invention provides a GraphRAG knowledge processing method and system based on multi-graph neural network ensemble learning, and belongs to the field of data processing.The GraphRAG knowledge processing system comprises a graph structure knowledge index construction module used for constructing a multi-modal index; the multi-GNN integrated retrieval module adopts at least two graph neural networks to perform parallel retrieval and fuse results; the multi-GNN integrated generation module is used for carrying out multi-dimensional feature coding and fusion by using another group of GNNs; and the model joint optimization module is used for optimizing the overall system performance through a multi-task learning framework. According to the invention, the processing capability and the answer quality of the GraphRAG system in a complex knowledge scene are obviously improved.

The present disclosure provides a knowledge processing method, system, storage medium and program product, and relates to the field of artificial intelligence. The method comprises: constructing a user knowledge graph according to historical operations of each user on knowledge in a public knowledge base; processing the user knowledge graph to obtain a user feature vector and a knowledge feature vector; obtaining an embedding vector matrix of a plurality of candidate knowledge based on the user feature vector and the knowledge feature vector; and performing knowledge recommendation for a target user based on historical operations of the target user on knowledge and the embedding vector matrix of the plurality of candidate knowledge.

The invention discloses an academic achievement authentication method and system based on a block chain, and relates to the technical field of block chains. The method comprises the following steps: receiving an academic achievement mutual identification request, and obtaining an authenticated student related label; querying a local training data table to obtain a standardized course named entity list; a target node training data table is loaded for retrieval and matching, and an authentication academic type label is obtained; performing encryption processing on student scores, identities, specialty and target course type labels by using a zero-knowledge processing technology, and generating a zero-knowledge voucher and a separated conversion code; and finally, sending the zero knowledge voucher through a block chain, and sending a conversion code to a target node through a short message to complete safe and verifiable academic achievement authentication. According to the method, automatic matching and efficient mutual recognition of cross-institution course credits are achieved, it is ensured that student privacy data are not leaked through the zero-knowledge proof technology, and the problems that in the prior art, efficiency is low, manual work is relied on, and the privacy leakage risk is high are solved.

The application discloses a kind of equipment knowledge management system and method;The system comprises: multi-modal data access module, for accessing multiple format files and extracting multi-modal elements;Knowledge processing module, for the structural treatment of extracted elements and constructs knowledge graph;Retrieval question and answer module, for executing user intent judgment based on user question input;According to the intention recognition result, when judging triggering question and answer, generate answer and its generation basis;Fault diagnosis module, for determining triggering fault diagnosis according to the intention recognition result, constructing fault tree according to knowledge graph and outputting troubleshooting scheme;Process application module, for determining triggering process application according to the intention recognition result, extracting BOM structure and process elements, generating process outline, multi-level process and SOP content, recommending associated resources based on process;Authority management module, for realizing access control based on directory and secret level.The application provides efficient and accurate equipment knowledge management platform for users.

The invention provides an industry agent construction platform and method, electronic equipment and a storage medium, and the platform comprises a role setting module which is used for determining the role and responsibility of an industry agent. And the workflow construction module is used for providing a visual interface for a developer, so that the developer constructs a workflow of the industry intelligent agent. And the private domain knowledge capability module is used for acquiring at least one private domain knowledge base and configuring at least one knowledge retrieval strategy, so that a developer configures private domain knowledge processing capability for the industry agent according to the at least one private domain knowledge base and the at least one knowledge retrieval strategy. And the safety protection module is used for carrying out sensitive information identification and desensitization on the input and output data of the industry intelligent agent. And the debugging and publishing module is used for providing a visual debugging interface, so that a developer debugs the industry intelligent agent through the visual debugging interface, a publishable platform is provided for the industry intelligent agent, and the developer selects the platform to publish the industry intelligent agent.

The invention provides a real-time risk monitoring method for bank transfer. The method can be applied to the technical field of block chains and the field of financial science and technology. The method comprises the following steps: in response to a transfer transaction request, converting the transaction request into a standardized event; broadcasting the standardized event to a smart contract cluster; obtaining a risk control decision result generated by the smart contract cluster for the standardized event; if it is determined that the risk control decision result is transaction release, generating a risk factor bitmap according to transaction data and the risk control decision result, and performing uplink evidence storage on the risk factor bitmap; and calling a tracking contract to perform on-chain real-time tracking on the fund flow direction, performing zero-knowledge processing on the tracking result, and broadcasting the tracking result to each node of the alliance chain to update a shared risk map, the shared risk map being used for providing associated risk data for the smart contract cluster. The invention further provides a bank transfer real-time risk monitoring device and equipment, a storage medium and a program product.

This invention discloses a system for converting tacit knowledge into explicit knowledge based on knowledge graphs and large models. It includes a knowledge system ontology modeling and management module for constructing and maintaining the knowledge system ontology model in large model applications; a data access and knowledge graph construction module for mapping and loading multi-source heterogeneous data onto the knowledge system ontology; an ontology virtual business environment engine module; a tacit knowledge mining and explicit knowledge generation module that, in a virtual environment, uses graph analysis and large model reasoning to mine tacit knowledge and generate explicit knowledge; and a business strategy planning and workflow orchestration module that transforms explicit knowledge into executable business strategy plans and workflow orchestrations. Through the knowledge system ontology modeling and management module, a systematic knowledge framework is constructed, achieving systematic accumulation of enterprise tacit knowledge, effectively preventing knowledge loss, and improving knowledge reusability and scalability.

The application discloses a method and system for automatically generating a video based on unstructured knowledge of multiple agents, relates to the technical field of video automatic generation based on knowledge processing, and automatically identifies repeated or contradictory knowledge fragments through a data source weight evaluation mechanism and a content semantic similarity calculation method, establishes a controversial knowledge unit list, and adopts a semantic vector similarity algorithm to analyze the matching degree of controversial content and a preset script.For the identified controversial knowledge points, a backup knowledge replacement algorithm is used to retrieve high-confidence replacement content from a reliable knowledge base, a knowledge unit replacement operation is performed, a high-quality video output with a controversial identifier is generated, and the content accuracy and reliability of the multi-source knowledge fusion video are effectively improved.The application realizes a whole-process quality control system from knowledge identification to video generation, realizes intelligent matching of knowledge reliability evaluation and video content presentation mode, and restricts practical deployment of the technology.

The invention discloses an equipment knowledge management system and method. The system comprises a multi-modal data access module used for accessing files in various formats and extracting multi-modal elements; the knowledge processing module is used for carrying out structured processing on the extracted elements and constructing a knowledge graph; the retrieval question and answer module is used for executing user intention judgment based on user question input; generating an answer and a generation basis thereof when judging that the question-answer is triggered according to the intention recognition result; the fault diagnosis module is used for constructing a fault tree and outputting a fault removal scheme according to the knowledge graph when judging that fault diagnosis is triggered according to the intention recognition result; the process application module is used for extracting a BOM structure and process elements, generating a process outline, multi-stage processes and SOP contents and recommending associated resources based on the processes when the process application is judged to be triggered according to the intention recognition result; and the authority management module is used for realizing access control based on the directory and the security level. According to the invention, an efficient and accurate equipment knowledge management platform is provided for the user.

The invention relates to a data processing method and system for anonymous person attribute abundance optimization, and relates to the field of data processing. Privacy ranking is performed on an investigation attribute set based on a predefined privacy series table to obtain a first sequence; a zero-knowledge processing data sandbox is utilized to process attribute feature value sets of to-be-selected personnel to obtain multiple groups of zero-knowledge feature value sets, a second sequence is obtained according to variance sorting of the feature value sets, the two sequences are combined to carry out serial number summation sorting to obtain a third sequence, and finally attribute abundance optimization is carried out according to the third sequence to realize personnel sorting. The technical problem that screening efficiency and privacy protection are difficult to balance when personnel screening is carried out on a group in a special scene is solved, the screening efficiency and privacy protection are effectively balanced, the accuracy of personnel screening is improved, and the risk of privacy disclosure is remarkably reduced.

The application discloses an industrial intelligent agent system and method fusing digital twin and a four-element core, belongs to the field of artificial intelligence, and comprises a digital twin perception layer, a four-element fusion core layer, a hybrid reasoning engine and an interpretable report generator.The digital twin perception layer is used for acquiring real-time state data of a physical entity; the four-element fusion core layer integrates OWL ontology modeling, graph database storage, large language model interaction and multi-physical field agent model, and generates a four-element collaborative knowledge processing result; the hybrid reasoning engine performs parallel rule reasoning, graph algorithm mining, large language model reasoning and agent model reasoning and fuses to generate a comprehensive reasoning conclusion; and the interpretable report generator generates a multi-modal report containing a reasoning path and physical evidence.The application realizes interpretable tracing of a decision-making process through four-element collaboration, realizes millisecond-level physical quantity prediction through an agent model, realizes continuous evolution of knowledge through a dynamic evolution module, and significantly improves the reliability, real-time performance and adaptability of an industrial intelligent system.

The application discloses an ICD intelligent coding method based on a multi-level knowledge-driven large language model, and belongs to the technical field of intelligent coding. The method comprises the following steps: S1, a sub-model matching knowledge base is constructed to select an adaptive sub-model for a diagnosis text; S2, a single diagnosis coding knowledge base is constructed, the adaptive sub-model is called, and a preliminary coding result is generated for a single diagnosis of the diagnosis text; S3, a global verification knowledge base is constructed to perform global verification on all preliminary coding results; and S4, the global verification result is input into a strong rule quality control engine to perform final verification and merging. The application optimizes the knowledge processing process, only filters and vectorizes effective characters that are strongly related to ICD coding when constructing the three-layer knowledge base, eliminates redundant and invalid characters, greatly improves the recall accuracy and efficiency of retrieval enhancement, and provides accurate knowledge support for model decision-making.

The invention relates to the technical field of knowledge processing, and discloses a data processing method and device based on non-causal priori, equipment and a storage medium, and the method comprises the steps: screening variable pairs with a non-causal relationship, and obtaining non-causal priori knowledge; on the basis of non-causal priori knowledge, data processing is inhibited from developing to an error edge, and the error edge is composed of variable pairs with a non-causal relationship. The device, the equipment and the storage medium all correspond to the method. According to the method, the performance of various causal discovery algorithms is improved, and the robust performance is shown in real application; non-causal edges are inhibited in the optimization process, so that the number of error edges caused by data noise is effectively reduced, especially in a high-dimensional scene; the reasoning ability of LLMs is combined with a data-driven causal discovery algorithm, and reliable constraints can be generated without expensive manual annotation.

In some implementations, a machine learning model (e.g., a knowledge processing system) can apply a reasoning technique to knowledge representations associated with cells (e.g., using a genetic algorithm) and predict a clinical outcome (e.g., for a patient). In some implementations, a method includes producing a cell population. Gene expression data for the cell population can be received. The gene expression data can be analyzed to identify a set of gene signatures. The set of gene signatures can be provided as an input to a machine learning classifier. A predicted clinical outcome can be generated.

The invention relates to a content generation method and device, and the method comprises the steps: starting a content generation task comprising a plurality of content generation sub-flows in response to a content generation request; executing the following steps in each content generation sub-process: executing knowledge processing operation according to a generation target and input information of the current content generation sub-process to obtain a knowledge processing result; inputting the knowledge processing result into an artificial intelligence model, and generating stage content of a current content generation sub-process; and determining target content meeting the content generation request according to the stage content generated by the plurality of content generation sub-processes. Therefore, the target content which is high in quality and highly meets the content creation requirement of the user can be output.

This invention discloses a blockchain-based method and system for certifying academic achievements, relating to the field of blockchain technology. The method includes: receiving a request for mutual recognition of academic achievements and obtaining relevant tags for certified students; querying a local training data table to obtain a standardized list of named entities for courses; loading the training data table of a target node for retrieval and matching to obtain certification academic type tags; encrypting student scores, identity, major, and target course type tags using zero-knowledge processing technology to generate a zero-knowledge credential and a separate conversion code; and finally sending the zero-knowledge credential via blockchain and the conversion code to the target node via SMS to complete secure and verifiable academic achievement certification. This invention achieves automated matching and efficient mutual recognition of course credits across institutions, ensuring the protection of student privacy data through zero-knowledge proof technology, and solving the problems of low efficiency, reliance on manual labor, and high risk of privacy leakage in existing technologies.

The invention relates to the technical field of knowledge management and artificial intelligence, and discloses a knowledge management system based on artificial intelligence big data. The system comprises knowledge flow capture, symbol reasoning, neural embedding, strategy synthesis and strategy deployment components. The system generates structured knowledge through multi-modal data acquisition and cleaning; performing symbolic reasoning by utilizing predicate logic and a rule base, and constructing a symbolic knowledge graph; a deep learning model is adopted to generate low-dimensional vector representation; fusing the symbolized knowledge graph and the vector representation, and generating a knowledge management strategy through a strategy gradient algorithm; and asynchronously executing the strategy in the cloud environment. According to the scheme, through combination of symbol reasoning and a neural network technology, interpretability and logic preciseness of a knowledge processing process are ensured, and meanwhile, the dynamic adaptive capacity and decision accuracy of system strategy generation are improved.

The application relates to the field of artificial intelligence and knowledge processing technology, and discloses a low-quality data optimization method and system for RAG question and answer evaluation, wherein the low-quality data optimization method for RAG question and answer evaluation comprises the following steps: user interaction data mining and mode extraction, hierarchical adversarial sample generation and testing, cross-validation and weak point atlas construction, targeted data enhancement and repair, feedback learning and continuous optimization. Through the multi-level adversarial sample generation technology combined with the actual user query mode, the application significantly improves the identification ability of factual errors, logical contradictions and boundary condition problems; can capture subtle semantic inconsistencies and context-dependent errors, greatly reduces the possibility of misleading answers generated by the RAG system, realizes accurate identification and effective repair of the RAG system data which is reasonable on the surface but actually has problems, and significantly improves the system answer accuracy.

Provide a system. 【Solution means】 Means for collecting and formalizing evaluation information of a knowledge processing system to be generated; Evaluation means for quantifying the performance of a knowledge processing system to be generated based on the evaluation information; Means for receiving a user's work procedure and usage purpose and clarifying requirements; Means for selecting an optimal knowledge processing system to be generated using the requirements and the evaluation information; Means for automatically generating and notifying information on the selected knowledge processing system to be generated as a document; Means for collecting opinions from users and using them to improve the accuracy of evaluation means after the next time; Means for collecting data for optimizing the performance of various knowledge processing systems in an automatic control device and selecting an optimal knowledge processing system; A system including the above.

This invention relates to the fields of artificial intelligence and data processing technology, specifically a knowledge processing method, system, and storage medium based on multidimensional semantic enhancement. The method includes acquiring a set of semantically segmented text; invoking a preset vectorization model to map the set of segmented text to a high-dimensional semantic vector space; invoking a trained pre-trained language model; and establishing a unique identifier mapping between the high-dimensional semantic vectors in the vector index library and the semantic entity nodes in the directed topological graph. This invention forms a dual-driven knowledge storage architecture by constructing a vector index library and a directed topological graph and establishing an association mapping between the two. This enables computers to recognize and utilize deep relationships such as preconditions and causality between knowledge entities, solving the problem of singular data representation in existing technologies.

The invention discloses a power equipment metal material failure analysis intelligent auxiliary system and a use method. The system adopts a four-layer architecture of a knowledge source layer, a knowledge storage layer, a knowledge processing layer and a man-machine interaction layer. The knowledge source layer stores information such as macroscopic images, standard specifications and failure cases in a classified manner according to failure modes; the knowledge storage layer guarantees data security and query efficiency through a backup mechanism and multivariate retrieval; the knowledge processing layer identifies a failure mode based on a convolutional neural network and dynamically optimizes an inference model; the man-machine interaction layer provides diversified input and output modes. According to the use method, efficient and collaborative failure analysis is achieved through the processes of information uploading, system analysis, supplementation and perfection, result application and feedback optimization. The system and the method have the advantages that the problems of scene splitting, low efficiency and the like in a traditional mode are solved, and the accuracy and the working efficiency of failure analysis of the metal material of the power equipment are improved.

The invention discloses a space-time signal classification and interpretation system and method based on retrieval enhancement generation, and belongs to the technical field of artificial intelligence and signal classification. The system comprises a signal data conversion module, a text knowledge processing module, an indexing and retrieval module and an enhancement generation module, wherein the signal data conversion module is used for generating a signal knowledge base; the text knowledge processing module is used for generating a text knowledge base, receiving documents for analyzing feature meanings and partitioning the documents by using a text knowledge partitioning strategy; the indexing and retrieval module comprises an indexing unit and a retrieval unit, and the indexing unit is responsible for processing block data obtained from the signal data conversion module and the text knowledge processing module and storing the block data in a vector database through word embedding vectorization; the retrieval unit is used for performing approximate nearest neighbor search and merging retrieval documents to improve the recall rate; and the enhancement generation module is used for splicing and integrating retrieval contents through LLM to obtain a signal classification conclusion and principle explanation.

This invention relates to the field of manufacturing knowledge processing technology, specifically to a method and system for vectorizing manufacturing equipment maintenance knowledge. The method involves: extracting document text and image text differentially through structural complexity assessment; extracting complete knowledge units from the current boundary to the next boundary using multi-modal semantic boundary matching rules while preserving hierarchical paths; determining brand affiliation through multi-source weighted voting, storing and vectorizing knowledge in batches by brand; using cosine similarity combined with thresholds and TOPK filtering during retrieval; and implementing brand-level routing and progressive degradation strategies to dynamically adjust thresholds and output quantity. This invention improves the semantic integrity of knowledge segmentation, cross-brand retrieval accuracy, and retrieval reliability, significantly reduces the risk of large model illusions, and achieves efficient and scalable vectorized construction of maintenance knowledge.