103 results about "Knowledge processing" patented technology

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 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 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 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.

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 invention provides a credible traditional Chinese medicine evidence-based diagnosis and treatment intelligent agent construction method, system and device, and relates to the technical field of traditional Chinese medicine evidence-based diagnosis and treatment intelligent agents.The method comprises the steps that text corpora in the traditional Chinese medicine field are collected and preprocessed through a natural language processing method; based on a large language model, performing knowledge processing on the text corpus; based on the pre-training data in the traditional Chinese medicine field, completing pre-training on the base large language model to obtain a large language model in the traditional Chinese medicine field; based on the traditional Chinese medicine field evidence-based diagnosis and treatment data, performing supervision fine tuning on the traditional Chinese medicine field big language model, and constructing a traditional Chinese medicine evidence-based diagnosis and treatment agent; based on a multi-dimensional diagnosis and treatment quality evaluation strategy, through an online reinforcement learning method, a traditional Chinese medicine evidence-based diagnosis and treatment agent is continuously optimized, and a credible traditional Chinese medicine evidence-based diagnosis and treatment agent is constructed. According to the scheme, the accuracy, the reliability and the continuous optimization capability of the traditional Chinese medicine evidence-based diagnosis and treatment intelligent agent can be remarkably improved.

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.