121 results about "Knowledge processing" patented technology

The invention relates to the technical field of data analysis, can be applied to business scenes of medical health, financial science and technology, culture research and the like, and discloses a multi-source knowledge processing and querying method, which comprises the following steps: data acquisition, cleaning and standardization processing, and standardized database construction; extracting core concepts and association relationships, and generating knowledge elements; constructing a multi-dimensional knowledge graph based on knowledge elements, and establishing a semantic index to realize data semantic annotation and bidirectional mapping; and analyzing the query intention, extracting a query constraint condition, and executing association reasoning based on the multi-dimensional knowledge graph to generate a query result. According to the method, the standardized database of the multi-source heterogeneous data is constructed, so that the data consistency is improved; through multi-dimensional knowledge graph construction and semantic index establishment, the relevance and structural expression of data are enhanced, so that the relationship between knowledge elements is clear and traceable; and through association reasoning based on query constraint conditions, the query accuracy and efficiency are improved.

The invention provides an entity link-based multi-source information association system and method in an agricultural scene, and belongs to the technical field of agricultural artificial intelligence, and the system comprises a data analysis module which constructs a multi-modal data analysis layer for data analysis, converts the analyzed data into a knowledge unit in a preset format through a Converter component, and stores the knowledge unit in the preset format; retaining an original semantic hierarchical structure and generating knowledge association anchor points; the graph construction module is used for constructing a cross-modal knowledge graph by utilizing knowledge association anchor points and an entity linking technology; the graph retrieval module is used for retrieving the cross-modal knowledge graph on the basis of a GraphRAG hierarchical retrieval technology; the result optimization module is used for optimizing the retrieval result to obtain an optimized retrieval result; and the result processing module constructs a low-code workflow engine based on the optimized retrieval result, further constructs an agricultural knowledge processing assembly line, and executes the agricultural knowledge processing assembly line to obtain an executable working scheme. And the processing efficiency of agricultural knowledge is improved.

The invention relates to the technical field of knowledge processing, and particularly discloses a knowledge proposition error correction method and system based on knowledge graph optimization upgrading, and the method comprises the steps: extracting effective information from multi-source knowledge data through employing entity linking, relation extraction and attribute alignment methods, and constructing an initial knowledge graph. Through semantic analysis based on deep learning, grammar, semantic and logic analysis is carried out on knowledge propositions, and a proposition element triple is generated. A graph neural network is utilized to encode triples, proposition vectors and neighborhood feature vectors are obtained, structural similarity is calculated accordingly, and proposition errors are detected in combination with rules and a statistical method. An integrated learning algorithm is adopted to classify error traceability, and an error correction decision is made in combination with multi-source evidence, so that an accurate error correction result is obtained, and the accuracy and reliability of knowledge propositions are improved; the error correction process is more logical and reliable, blind error correction is avoided, and the quality and efficiency of knowledge proposition error correction are improved.

The invention relates to the technical field of artificial intelligence, and discloses a professional knowledge question and answer intelligent customer service system based on a self-optimization mechanism. The system comprises a user intention analysis module, a knowledge processing module, a self-optimization learning module and an interactive presentation module. A semantic understanding unit of the user intention analysis module generates a user intention signal; after the knowledge processing module receives the signal, a knowledge retrieval unit outputs related knowledge fragments and confidence, an answer generation unit forms candidate answers, and a quality evaluation unit determines an optimal answer according to the confidence; in the self-optimization learning module, a feedback analysis unit adjusts answer generation parameters according to user interaction data, a strategy adjustment unit optimizes a retrieval strategy in combination with an optimal answer and a historical dialogue, and a knowledge updating unit updates a knowledge base depending on an external knowledge source; and a multi-round dialogue management unit of the interactive presentation module adjusts a dialogue process, and a visual presentation unit outputs a natural language text and collects user feedback to a feedback analysis unit.

The invention discloses an electric power big data automatic reasoning platform and an electric power distribution system, and relates to the technical field of electric power systems, and the platform comprises a knowledge acquisition unit which collects and preprocesses electric power internal and external data, and converts the data into structured data through a knowledge processing unit; organizing the triple data by the dynamic knowledge graph construction unit to form an initial graph; the updating unit monitors a new dynamic state in real time and corrects or adds atlas content; the reasoning unit is based on the dynamic graph, power fault accurate reasoning and future demand trend prediction are achieved through a fault diagnosis and demand prediction algorithm, efficient integration and dynamic evolution of power knowledge are achieved through construction and real-time updating of the dynamic knowledge graph, timeliness and accuracy of the graph are ensured, and reliable data are provided for fault diagnosis; through a closed-loop architecture of data acquisition-inference analysis-scheme making-execution control, an intelligent sensor and an optimization algorithm are combined to generate a distribution scheme adaptive to a scene, and the power distribution adaptability and economy are improved.

The invention relates to the technical field of artificial intelligence, in particular to a culture field dynamic ontology intelligent construction method based on a large model, and the method comprises the following steps: constructing a relation network based on vocabulary semantic embedding, generating a graph to recognize a hyponymy and correct the hyponymy, determining a priority in combination with a context evaluation extension demand, and deducing semantic relation to optimize structural connection. And outputting a dynamic update sequence, and identifying a new entity matching inference rule to obtain an updated ontology structure. According to the method, vocabulary similarity is analyzed through semantic embedding, a cultural entity relation network is constructed, entity hyponymy and hyponymy are recognized in combination with atlas analysis, entity attributes are adjusted in real time, an ontology structure is optimized, it is ensured that an ontology can be flexibly expanded and adapt to a changing cultural environment, the adaptability and updating capacity of cultural knowledge are improved, the ontology structure is continuously improved, and the ontology effect is improved. Intelligentization and real-time performance of the scheme in practical application are enhanced, and accuracy and comprehensiveness of knowledge processing in the cultural field are improved.

The invention provides a water conservancy knowledge structured extraction and verification method and device, and belongs to the technical field of artificial intelligence, and the method comprises the steps: carrying out the differential text processing of different formats of files, and generating an intermediate file; classifying the intermediate file into a regulation class or a non-regulation class based on a preset rule base; performing hierarchical title identification on the regulatory files to form entry knowledge blocks, and converting table contents into HTML (Hypertext Markup Language) knowledge blocks; performing semantic segmentation on the non-regulation file to generate knowledge blocks; performing knowledge block checking and filing, and marking an abnormal alarm block; converting the table knowledge blocks into natural language description by utilizing a large model; and positioning the context of the original text of the alarm knowledge block, and performing intelligent correction through a large model. According to the method, a traditional semantic analysis model and a large language model are creatively fused, a closed-loop process of preprocessing, extraction, verification and correction is formed, the problems of structured analysis and error correction of complex texts in the water conservancy field are solved, and the knowledge processing efficiency and accuracy are remarkably improved.

The invention relates to the technical field of artificial intelligence education, and discloses a personalized online education system and method based on artificial intelligence, and the system comprises a data collection and perception module which is used for collecting the dynamic behavior data and multi-mode perception data of a learner; the knowledge processing and constructing module is used for processing teaching contents to construct a structured knowledge graph; the user modeling module is used for constructing a dynamic learner portrait comprising a knowledge state model and a cognitive-emotional state model for the learner based on the collected data and the constructed knowledge graph; and the intelligent decision and intervention module is used for generating and executing personalized learning intervention based on the dynamic learner portrait. According to the method, by fusing multi-mode cognitive state perception, reinforcement learning intervention decision and a knowledge graph dynamic evolution mechanism, accurate and timely personalized intervention for learners and intelligent guidance of optimal learning strategies are realized.

The invention discloses a bank intelligent operation knowledge base implementation method and system based on a large language model and RAG, and the method comprises the steps: firstly extracting business terms from structured, semi-structured and unstructured multi-source heterogeneous multi-modal data of a bank, and then constructing a business dictionary containing term similarity data and an ontology tree; quantitatively calculating the release mechanism weight, the timeliness coefficient and the punishment association degree of the supervision clauses to obtain authority values, and sorting the authority values; then using a double-constraint loss function to finely adjust the pre-trained large language model as a vector representation model, vectorizing service data, and storing the vectorized service data into a vector database; and finally, aiming at user query, retrieving in a vector database, rearranging in combination with a supervision clause sorting result, and generating a business response after compliance verification. According to the method, the bank unstructured knowledge processing capability and retrieval precision can be improved, and efficient intelligent operation is realized.

The invention discloses a knowledge base construction method, a knowledge processing method and a related product. The construction method comprises the following steps: acquiring a plurality of first documents included in a first knowledge base; integrating the plurality of first documents to obtain a plurality of different document sets, wherein each document set in the plurality of different document sets comprises the first documents with semantic association relationship; carrying out inductive reasoning on the first document included in each document set based on the large language model and the document generation instruction to obtain a second document corresponding to each document set; and constructing a second knowledge base based on the plurality of first documents and the second documents corresponding to each document set. Therefore, the cross-document reasoning ability can be introduced, and the knowledge hierarchy of the second knowledge base is expanded through the induction reasoning ability of the large language model, so that the second knowledge base contains more information to meet the use requirements of the large language model, and the accuracy of the output result of the large language model is improved.

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 an AI processing method and system for long-term memory of mechanical design knowledge, and the method comprises the steps: carrying out the semantic analysis and feature extraction of heterogeneous knowledge, such as parameterization formulas, engineering charts, technological processes and design principles, in the field of mechanical design through a multi-agent collaborative learning system; and establishing a multi-dimensional modular knowledge base and context-based Prompt strategy coupling mechanism. The method solves the problems of low efficiency, insufficient analysis accuracy, limited innovation support capability and the like in the existing mechanical design knowledge processing technology, and particularly solves the technical problems of high calculation complexity, inaccuracy in reasoning, poor adaptability and the like when multiple types of design knowledge are processed. Through the implementation of the method, the processing efficiency of the design knowledge and the design automation level are remarkably improved, the technical threshold of a designer is reduced, the design period is shortened, efficient analysis, accurate matching and innovative application of the mechanical design knowledge are achieved, and powerful support is provided for intelligent development of mechanical design.

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 invention discloses a multi-modal large model text image data knowledge processing method and device for RAG, and the method comprises the steps: recognizing correct characters from a text watermark image, automatically generating a character data set corresponding to the text watermark image, and forming an image-text sample pair training sample; an enhancement strategy is introduced into the generated image-text sample pair, and the diversity and adaptability of a training sample are enhanced through preprocessing; integrating all the enhanced training sample data, dividing the data into a training set, a verification set and a test set in proportion, and performing training, parameter adjustment and performance evaluation on the multi-model large model; and inputting a text watermark image and a corresponding language instruction into the trained multi-modal large model, and reasoning and outputting correct text content by the multi-modal large model. According to the multi-modal fusion technology, the internal relation between the watermark and the text can be deeply mined, the accuracy and the effect of watermark elimination are greatly improved, and meanwhile, the integrity of text information is reserved.

The invention discloses a cultural relic knowledge processing method and a related device, and relates to the field of big data, and the method comprises the steps: obtaining cultural relic text data corresponding to to-be-processed cultural relic knowledge, carrying out the text embedding of the cultural relic text data through employing a pre-training word vector, obtaining a cultural relic word vector, inputting the cultural relic word vector into a pre-trained encoder of an improved Transform model, and carrying out the text embedding of the cultural relic text data. And mapping the word vectors into a group of context-aware target word vectors, and inputting the target word vectors into a decoder of the improved Transform model for decoding to obtain a cultural relic knowledge processing result. According to the method, automatic processing of cultural relic knowledge is realized, the weight of the feedforward network is initialized by adopting a quantum spin optimization algorithm to ensure the stability of weight initialization, multi-dimensional features in cultural relic text data are processed by adopting an interlayer nonlinear coupling constraint loss function, and the processing speed is accelerated by adopting a quantum acceleration gradient updating mechanism. Therefore, large-scale and multi-dimensional cultural relic knowledge can be efficiently processed.

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 invention discloses a large model knowledge base operation system based on multi-role cooperation and dynamic optimization. The system comprises a user interaction module used for receiving knowledge requirements triggered by user feedback and identifying knowledge gaps through semantic analysis; the multi-role cooperation module is used for defining roles and permissions thereof, generating knowledge optimization tasks according to a current knowledge gap, and distributing the knowledge optimization tasks to the roles so as to supplement optimized knowledge contents through the roles; the knowledge processing module is used for processing and analyzing the optimized knowledge content; the knowledge storage module is used for carrying out structured and unstructured mixed storage on the knowledge content which is qualified in processing and analysis; and the large model interface module is used for synchronizing the optimized knowledge content to a large model training or reasoning link in real time. According to the method, efficient collaboration of editing and expert opinions can be realized through a large model knowledge base with multi-role collaboration, and the accuracy and timeliness of knowledge contents are ensured.

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 present invention discloses a structured data modeling method, modeling system, and management method. The method comprises: constructing a knowledge processing link model based on structured data; constructing a knowledge label matrix model based on the knowledge processing link model; performing instantiation determination on the knowledge label matrix; and arranging the structured data and the knowledge label matrix after instantiation determination to perform data set entity placement, thereby completing structured data modeling. The method effectively handles the processing link from data to information and then to knowledge, and automatically completes the construction of the knowledge label system and the knowledge link during the modeling process, laying a solid data model foundation for the subsequent research and development of applications such as knowledge search and intelligent recommendation.

The invention relates to the field of computing, in particular to a knowledge processing method and computing device.The knowledge processing method comprises the steps that at least one first document belonging to at least one document type is obtained; converting the first document into a second document according to a preset target document type to obtain at least one second document corresponding to the at least one first document; extracting at least one question and answer pair in the at least one second document, wherein the question and answer pair comprises a question and a first answer corresponding to the question; according to the at least one question and answer pair, a knowledge base is updated / generated, and the knowledge base is used for knowledge questions and answers. In the embodiment of the application, through document conversion, more documents participate in the establishment of the knowledge base, so that the source of the content of the knowledge base is more diversified, the comprehensiveness of the knowledge base is improved, and knowledge questions and answers with richer content can be provided through the knowledge base.

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.

Embodiments of the present invention relate to a knowledge processing method and device that combines user feedback with contextual learning. The method includes: recording a knowledge base used by a large language model as a first knowledge base; performing contextual knowledge learning based on a user-input instruction text and the first knowledge base, and inputting the learned knowledge sequence as instruction prompt text information along with the instruction text into the first model for task processing and outputting a corresponding generated text; and when the user is satisfied with the generated text, inputting the instruction text and the generated text into a knowledge extraction instruction template for instruction assembly, and inputting the obtained instruction text into the first model for knowledge extraction. Based on the extracted knowledge, the knowledge base is queried for old knowledge records, and whether the obtained query record is empty is determined. If so, knowledge is added to the knowledge base based on the extracted knowledge; otherwise, knowledge is updated in the query record based on the extracted knowledge. This invention can improve the timeliness and generalization of knowledge.

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.