181 results about "Knowledge content" patented technology

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of medical health, financial science and technology, culture research and the like, and discloses a content generation and optimization method based on a knowledge graph, which comprises the following steps: constructing a multi-source knowledge database, extracting core concepts and knowledge contents, and constructing the knowledge graph. Performing semantic analysis to generate semantic vector representation and a keyword list; retrieving the associated text fragment based on the semantic vector and the keyword list, and inputting the associated text fragment into a generation model to generate initial answer content; and utilizing the knowledge graph to match the domain entity and the knowledge graph node, generating a logical reasoning path, optimizing the initial answer content, and generating the final answer content. According to the method, content generation of accurate retrieval, deep knowledge association and logical reasoning enhancement is realized by fusing a multi-source knowledge database, knowledge graph reasoning and generation optimization; semantic vector matching and keyword retrieval are combined, so that the accuracy of knowledge acquisition is improved; and through knowledge graph reasoning path construction, the answer logic is coherent.

The invention specifically relates to the technical field of natural language processing, and discloses an intelligent interactive customer service system based on an AI large model, which comprises a multi-modal input analysis module, an intention preliminary detection module, a large model semantic understanding module, a dynamic knowledge base association module, a dialogue strategy generation module, a natural language generation module and a service feedback work order module, through deep cooperation of a multi-modal input analysis module and a large model semantic understanding module, entity and attribute information is accurately extracted, context semantic association information is mined, and through the cooperative effect of an intention preliminary detection module, a dynamic knowledge base association module and a dialogue strategy generation module, based on a semantic analysis result output by a large model, a dialogue strategy is generated. According to the method and the system, matching calculation is carried out with the constructed dynamic knowledge base, rich knowledge support is provided for solving complex problems, personalized knowledge content is recommended for different users through the natural language generation module and the service feedback work order module, and the reply matching degree and the complex problem processing capacity are greatly improved.

The invention discloses an intelligent document generation system and method for bidding documents, and the system comprises a preprocessing module which is used for obtaining bidding document files in various formats, and converting the obtained bidding document files in various formats into structured bidding document files; the analysis module is used for analyzing the converted bidding document file based on the large model cue word to obtain a structured bidding document file analysis result; the directory generation module is used for generating a directory of the bidding document file according to the analysis result; the retrieval module is used for generating a corresponding knowledge content set according to the bidding document file directory; and the content generation module is used for generating the text content of the bidding document file based on the knowledge content set and the structure information of the bidding document file directory. And the content assembly module is used for performing multi-dimensional feature extraction and classification on the generated bidding document file text content, and completing content assembly according to a preset document structure tree to obtain a standard document meeting bidding document requirements.

The invention discloses a cloud management and intelligent distribution method for classroom teaching resources, and relates to the technical field of cloud computing software. The classroom teaching resource cloud management and intelligent distribution method comprises the steps that S1, multi-source teaching resource data and auxiliary distribution data are acquired and preprocessed, and a knowledge content database is constructed; s2, performing semantic fusion analysis through text semantic association, structural consistency and professional term coverage data; s3, carrying out dependency evaluation by fusing pre-association, knowledge co-occurrence, sequence association and semantic fusion data; s4, performing resource adaptability distribution analysis through the maximum knowledge dependence value in combination with the learning state data and the historical feedback data; and S5, evaluating the teaching resource quality by collecting classroom feedback, teacher evaluation and resource use data, and implementing content optimization. The problems of semantic distortion, path breakage, distribution mismatching and resource updating inconsistency in the teaching resource data fusion and intelligent resource distribution process are solved.

The invention relates to the technical field of health assessment, and discloses a user climacteric physical and psychological health assessment and science popularization system, which comprises a science popularization plot and dynamic assessment process module, a multi-dimensional assessment engine and a general knowledge and personalized knowledge content push engine which are in closed-loop communication connection in sequence. According to the application, the science popularization garden and dynamic evaluation process module not only ensures data integrity, but also adapts to real-time updating requirements of medical guidelines; the multi-dimensional assessment engine fuses the multi-dimensional data and processes the medical scale, so that more comprehensive and accurate health assessment is realized; a general knowledge and personalized knowledge content pushing engine constructs a dynamic user portrait based on multi-dimensional data and evaluation results, and realizes accurate matching and interpretable pushing of health knowledge through a tag system and a four-dimensional evaluation system; the flexibility and the operation efficiency of the evaluation system and the acceptability of the user to the health management content are improved, and a finer and more efficient physical and psychological health doctor-patient management scheme is provided for climacteric people.

The invention relates to the technical field of dialogue robots, and provides a big language model dialogue robot-based data processing method and related equipment, and the method comprises the steps: carrying out the text conversion and vectorization processing of voice input content, and obtaining text data and vector representation; performing similarity retrieval on the vector representation and vector data in a preset vector database to obtain associated knowledge content; performing keyword and key demand screening on the text data to generate cue words, and inputting the associated knowledge content and cue words into a preset large language model to generate a natural language answer text; and converting the natural language answer text into voice information and outputting the voice information. Through the scheme, the understanding of the voice input content of the user and the generation of the natural language answer are realized, and the problems of time and labor consumption in knowledge base construction and mechanization of the dialogue content due to the fact that an existing dialogue robot extracts predefined content or pre-recorded text from a knowledge base to answer the user are solved.

The invention provides an enterprise-level unstructured knowledge governance-oriented method and a storage medium. The method comprises the steps that an initial document is input into a visual language model for layout analysis, and document structure information of a target document is obtained; segmenting the document structure information to generate text slices to be vectorized; metadata extraction is carried out based on the text slices, and structured knowledge content vectors are generated; and performing index configuration according to the knowledge content vectors to form enterprise-level knowledge governance standards. According to the method, the document structure is analyzed through the visual language model, the text slices are generated through the intelligent segmentation algorithm, the knowledge vector is constructed through metadata extraction, and the mixed index configuration is performed, so that the problems of inaccurate layout analysis, logic structure damage and low retrieval efficiency in the traditional technology are effectively solved, and the method has the advantage of improving the knowledge management precision and availability.

The present disclosure provides a cross-file question and answer knowledge extraction method and system, and an electronic device. The method includes: obtaining a user question; converting the user question into a user question embedding vector by using an embedding function; determining the user question embedding vector and a first similarity vector of a root node of a file embedding vector tree of each professional knowledge file; determining a plurality of similar vector trees by using a K-nearest neighbor algorithm based on first similarity vectors of all root nodes; determining a candidate node set by using the K-nearest neighbor algorithm based on all the similar vector trees; determining an optimally-matched node set based on the candidate node set; and determining, based on the optimally-matched node set, file knowledge content corresponding to the user question. The present disclosure improves accuracy of extracting the cross-file question and answer knowledge.

The invention provides a periodical knowledge graph construction method, a periodical knowledge question-answering method and a periodical knowledge graph construction device. The periodical knowledge graph construction method comprises the following steps: performing sequence labeling method knowledge extraction on an obtained periodical text to be processed to obtain a knowledge labeling sequence; performing vocabulary network strategy entity alignment on the knowledge labeling sequence to obtain an aligned knowledge sequence, performing priority strategy entity disambiguation on the aligned knowledge sequence to obtain a disambiguation knowledge sequence, and performing knowledge reasoning completion on the disambiguation knowledge sequence to obtain integrated journal knowledge; and performing knowledge graph construction according to the integrated periodical knowledge to obtain a periodical knowledge graph. Primary knowledge extraction is carried out through a sequence labeling method, knowledge entities of different data sources are aligned through a vocabulary network strategy, periodical knowledge of different sources can be effectively integrated, ambiguous content between entities is eliminated through priority strategy entity disambiguation, missing values and blank values are complemented through knowledge reasoning, the knowledge content can be effectively verified, and the accuracy of the periodical knowledge is improved. Therefore, the data quality of the periodical knowledge graph is improved.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a dynamic state portrait driven service optimization method, device and equipment and a medium. And constructing a dynamic state portrait of the individual, analyzing the state portrait to generate a state abnormality level, adjusting strategy optimization service parameters according to the state abnormality level and the service parameters, and matching knowledge contents based on the state data and the abnormality level to output guidance information. According to the method, the multi-source state data of the individual is integrated, the state portrait is dynamically constructed, and the state abnormal level is identified, so that the self-adaptive adjustment of the service parameters and the personalized matching of the knowledge content are realized, and the timeliness and pertinence of service customization are improved.

The invention discloses an artificial intelligence question answering system and method based on multi-knowledge-base association. The method comprises the following steps: acquiring a question input by a student; preprocessing the questions, including operations of word segmentation, part-of-speech tagging, stop word removal and the like; identifying a plurality of knowledge points and themes involved in the questions; associating a plurality of related knowledge bases based on the identified knowledge points; carrying out vectorization processing on the questions and the content in the knowledge base, and constructing high-dimensional vector representation; matching the question vector with the knowledge base vector by using a vector database, and retrieving knowledge content most relevant to the question; based on the retrieved knowledge content, adopting a generative pre-training model to generate a high-quality answer; and feeding back the generated answer to the student, and collecting the evaluation and feedback of the student on the answer to continuously optimize the system performance. According to the method, complex questions related to multiple knowledge points can be effectively processed, and the matching degree and the answering quality of the question answering system are improved through a multi-knowledge-base association and vectorization matching method. According to the method, the limitation of a single knowledge base and simple text slice reasoning in the prior art is overcome, the artificial intelligence question-answering system has higher intelligence and adaptability, and the constantly changing requirements in the education field are better met.

The invention discloses a knowledge space control method and system for assisting learning, and relates to the technical field of knowledge space generation methods, and the method comprises the steps: determining a corresponding problem solving path according to the previous problem solving content of a user; and determining error contents of each problem solving node in the problem solving path based on matching of the problem solving path and the knowledge application space, and marking knowledge nodes associated with the error contents. Determining corresponding correct content according to the error content and knowledge content presented by the knowledge node, determining difference content between the correct content and the error content, determining a correct answering thought according to the difference content and the answering thought of the user relative to the error content, and marking knowledge difficult points of the user; the error factors of the user are determined according to the knowledge difficult points of the user, the corresponding mastering level and the answering accuracy of the user, the corresponding auxiliary learning measures are determined based on the error factors of the user and the current learning process of the user, and the accuracy of the auxiliary learning measures is improved.

The invention provides a data acquisition method and device, electronic equipment and a product, and is applied to the technical field of model training. The method comprises the following steps: extracting a plurality of first questions and a plurality of knowledge contents from a knowledge text, and constructing a plurality of second questions according to each knowledge content; optimizing each second problem and each first problem to obtain a plurality of target problems; determining at least one piece of knowledge content corresponding to each target question, wherein the at least one piece of knowledge content corresponding to the target question comprises an answer of the target question; and according to each target question and the corresponding at least one knowledge content, constructing question and answer data corresponding to each target question, the question and answer data being used for training a model.

The invention relates to an electric power intelligent knowledge retrieval method and device based on an RAG model, computer equipment, a computer readable storage medium and a computer program product, and can be applied to the technical field of computers. The method comprises the steps of obtaining a query request; performing semantic analysis processing on the query request to obtain a query semantic feature of the query request; according to the query semantic features, candidate knowledge content is retrieved from a pre-constructed electric power knowledge base; screening the candidate knowledge content to obtain a target retrieval result of the query request; inputting the target retrieval result into a pre-trained power field content answer model for content answer processing to obtain preliminary answer content of the query request; and performing security filtering processing on the preliminary answer content to obtain a target answer result of the query request. By adopting the method, the power knowledge acquisition efficiency can be improved.

The invention relates to the field of artificial intelligence, in particular to an AI-based nursing knowledge interesting courseware generation method and system. The method comprises the following steps: firstly, constructing an AI model library, and packaging input parameters and output parameters of each AI model in the model library; the nursing knowledge is uploaded to the system; creating a corresponding abstract task for nursing knowledge, and operating an AI model to obtain high-quality knowledge key points; supplementing cue words for the knowledge key points, and providing the cue words to an AI large model to generate materials; performing structured arrangement on courseware themes, chapters and contents by applying a mind mapping method, packaging the courseware themes, chapters and contents into AI model input parameters, and performing automatic layout through the AI model to generate a PPT file; and adjusting the PPT file, outputting the PPT file as courseware, and editing and processing courseware content. The AI model technology is utilized, key knowledge content can be quickly extracted, rich teaching materials can be generated, the courseware making method is optimized, the input of teaching group course making is effectively reduced, the courseware quality is improved, and the professional level of nursing personnel can be effectively promoted to be improved.

The embodiment of the invention provides an information processing method and computing equipment. The method comprises the steps of obtaining user input content; determining a target knowledge base which can be accessed by the user in combination with the user feature information and the knowledge base feature information; searching target knowledge content matched with the input content from the target knowledge base; and generating feedback information by using a large language model according to the target knowledge content and the input content. According to the technical scheme provided by the embodiment of the invention, the accuracy of the large language model is improved, and the data security is ensured.

The invention relates to the technical field of computers, and discloses a knowledge base-based authority control method, device and equipment and a medium, and the method comprises the steps: obtaining a to-be-accessed target knowledge base and a user identity information set, and carrying out the grading processing of the knowledge content in the target knowledge base through a natural language model, and obtaining a plurality of knowledge categories; determining an initial user identifier corresponding to each piece of initial user identity information in the user identity information set, and establishing a corresponding relationship between each initial user identifier and the knowledge category; receiving an access request of a target knowledge base, determining a target user identifier from the user token information in the access request, and determining an authorized target knowledge category from the corresponding relationship according to the target user identifier; and performing legality verification on the access request, and if the verification is passed, allowing the access request to access the knowledge content corresponding to the target knowledge category. The method can be applied to financial science and technology and medical care service program systems, and fine-grained permission allocation and access verification can be achieved.

The embodiment of the invention relates to the technical field of information, in particular to an SQL resource estimation method, device and equipment based on a large model, and the method comprises the steps: receiving an SQL statement input by a user, correcting a grammar error, and outputting a correct SQL code; analyzing fields, functions and limiting conditions in the SQL codes by configuring a large language model of a Python code executor tool; python codes are automatically written according to fields and limiting conditions, an operation environment is configured and executed, the size of a source data table is read, data are screened according to the limiting conditions, and the size of a screening table is obtained; according to the static parameters of the function, retrieving the original knowledge content to obtain an original knowledge set containing the Spark principle and historical execution data; and estimating resource parameters based on the SQL static parameters, the double-table dimension information and the original knowledge set. Spark parameters are generated through principle calculation and historical verification, and accurate resource configuration, cluster management and control and multi-field application requirements are met.

The invention relates to the technical field of big data evaluation, in particular to an AI educational training analysis method and system based on big data evaluation, and the method comprises the steps: obtaining a weak link of the operation of a corresponding person from historical operation data, constructing an operation weak link knowledge point graph based on the knowledge content related to the weak link, and obtaining an AI educational training analysis result; performing weak knowledge point association analysis based on the operation weak link knowledge point graph to obtain association conditions of the weak knowledge points, and performing importance weight analysis of the weak knowledge points based on the association conditions of the weak knowledge points and the risk levels of the corresponding weak links obtained through evaluation. The course resource matching analysis is carried out based on the importance weight analysis of the weak knowledge points, the danger degree of weak links is evaluated, and the course resource matching is carried out according to the importance weight of the weak knowledge points, so that personnel can learn and master key knowledge and skills in time, and the risk of accidents caused by misoperation is reduced.

The invention relates to the technical field of knowledge base generation, and particularly discloses an education knowledge base content generation method and system based on AI big data. The method comprises the following steps: comparing user answer content with answer information to obtain a matching degree, calibrating a positive sample and a negative sample to train an evaluation model, and determining a reference standard score according to a quantitative relationship between the positive sample and the negative sample; and screening the plurality of candidate knowledge contents based on the reference standard score and the tolerance threshold to calibrate the candidate knowledge contents as stable knowledge contents or to-be-corrected knowledge contents, and outputting the stable knowledge contents or the to-be-corrected knowledge contents. According to the method, the evaluation system based on the real answer data of the user and the evaluation standard reflecting the actual application effect of the knowledge content are constructed, and the evaluation standard is automatically calibrated according to data distribution, so that objective screening and continuous iteration of the knowledge content are realized, and the accuracy and reliability of the knowledge base content are improved.

The invention relates to the technical field of voice semantics, and discloses a dialogue intention recognition method and device based on a large model, equipment and a medium, and the method comprises the steps: recognizing a target first-level intention label of a target query text through SFT; determining a target knowledge block according to the knowledge base and the target first-level intention label; and determining a dialogue intention according to the RAG and the target knowledge block. Through the above mode, effective preliminary intention recognition is performed on the target query text through the SFT, the target first-level intention label is determined, the target second-level intention label is accurately determined in combination with the preset knowledge base and the RAG model, the intention recognition accuracy and fineness are improved, and the intention recognition efficiency is improved in the second-level intention recognition process. The method can focus on the knowledge content highly related to the target query text, and reduces the burden of processing irrelevant information by the RAG model. The method can be applied to the business fields of financial science and technology, medical health, old-age care and the like, and the user intention recognition accuracy of the intelligent customer service system is improved.

The invention discloses a teaching content generation method and system based on large model instruction and context knowledge dual drive. The method comprises the following steps: firstly, analyzing, slicing and vectorizing an original knowledge document in the education field through knowledge preprocessing in the education field; then, defining teaching content to generate a prompt word template, and defining a large model instruction, a variable and a context knowledge content block; secondly, arranging teaching content to generate a workflow, and constructing large model instruction driving and context knowledge driving logic; and finally, implementing dual-drive teaching content generation and performing result post-processing. Based on the method, a system corresponding to the method is constructed, and the system comprises an education field knowledge preprocessing module, a teaching content generation prompt word template definition module, a teaching content generation workflow arrangement module, a teaching content generation implementation and result post-processing module and a user man-machine collaborative interaction operation module. According to the method, the teaching content can be generated according with the education rule, the specific teaching scene requirement is met, and the teaching content generation accuracy and applicability are improved.

The invention discloses a domain knowledge content generation method and system based on retrieval enhancement generation, and belongs to the technical field of natural language processing and knowledge generation. Performing fuzzy semantic retrieval in the structured knowledge base to obtain semantic matching entries and calculate semantic relevancy; constructing a semantic fusion representation vector to form an enhanced representation set; performing context alignment with the query vector, and extracting a causal path fragment with the maximum weight; inputting the causal path and the query vector into a large language model, and executing a condition generation operation; analyzing and judging whether the generated content has term jump or logic chain scission or not based on the term dependency graph, if so, adjusting a context window and regenerating, and finally outputting professional content meeting dependency consistency; according to the method, the accuracy and logic consistency of professional field text generation are effectively improved, and the method is suitable for knowledge generation tasks in complex semantic scenes.

The invention discloses a knowledge base processing method based on a model, electronic equipment and an intelligent agent, and relates to the technical field of artificial intelligence, the intelligent agent can be embedded into an application program or an operating system to serve as a part of the application program or the operating system, and the intelligent agent is used for executing the following processing: obtaining input information; converting the input information into a first coding sequence; key values of all codes in the first code sequence are calculated in sequence to form a first key value set, and if a target mark exists in the input information, a second key value set of knowledge content of a target object indicated by the target mark is loaded to form a second key value set of knowledge content of the target object; the second key value set and the first key value set are combined to form a third key value set; reasoning a second coding sequence based on the third key value set; wherein the second key value set of the knowledge content of the target object comprises the key value of each code in the knowledge content stored before the input information is obtained.

The invention relates to the technical field of cultural relic analysis, and discloses a cultural relic knowledge extraction and visualization method, which comprises the following steps: processing an original sentence to obtain a feature vector and relation information of the sentence, inputting the relation information and the feature vector into an attention unit, and distributing different weights to context information of a current relation; fusing the feature vectors of the sentences output by the attention unit and the relation information to realize cultural relic knowledge extraction; constructing a visual view based on the identified data; the problems of particularity of knowledge content and text word formation in the cultural relic field, structure looseness and knowledge overlapping are solved; the extracted cultural relics are only explored and visualized, information of the cultural relics is displayed in a visual interaction mode, a user is helped to understand characteristics and evolution trends in the cultural relic development process under the historical culture background, repeated work of the user on cultural relic knowledge exploration is reduced, and the user experience is improved. And the analysis efficiency and exploration depth of the cultural relic knowledge by the user are improved.

The present invention discloses a method for intelligently generating an ontology, and its steps include: 1) converting the elements for describing entities in the XSD document to be processed into class nodes; converting the elements for describing entity attributes in the XSD document to be processed into data attribute nodes; 2) determining the edges between the nodes corresponding to each element according to the nested hierarchical relationship between the elements in the XSD document to be processed, and generating a directed graph corresponding to the XSD document to be processed; 3) generating semantic embedding vectors for each node in the directed graph, calculating the semantic similarity between nodes according to the semantic embedding vectors of the nodes; merging the nodes with semantic similarity greater than a set threshold into cluster nodes; 4) obtaining an ontology of resource knowledge content described in OWL language according to the directed graph processed in step 3). The present invention can reveal more knowledge content in the original XML resources and improve the description and revelation ability of the ontology for the original knowledge content.

The application provides an intelligent processing method and device for auditing problem qualitative analysis and rectification tracking based on a large model and a medium. It belongs to the technical field of auditing. The system comprises a model construction module: an intelligent auditing knowledge cloud brain is constructed, and knowledge base data is generated; based on the knowledge base data, key auditing element extraction is performed on the auditing business scene, and auditing element extraction result data is generated; auditing problem matching model training is performed according to the auditing element extraction result data, and an auditing problem accurate matching model is constructed; relying on the powerful knowledge base and intelligent matching capability of the large language model, knowledge content closely related to the problem is rapidly and automatically filled in, covering key information such as problem name, manifestation form, problem qualitative analysis, qualitative analysis basis and treatment and punishment basis, which greatly saves the time of auditing personnel for manually searching and sorting data, more ensures the accuracy and integrity of the problem description, and lays a solid foundation for subsequent auditing analysis.

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 knowledge management method and system based on information intelligent retrieval, relates to the field of data processing, and comprises the following steps: importing historical input modal data of a permission user within a current period for retrieval; adopting a modal recognition algorithm to count the frequency of various types of modal data in the historical input modal data, and determining the dominant input modal of the permission user; constructing a knowledge conversion rule model according to the retrieval expression of the dominant input modal; connecting an initial knowledge base of an information intelligent retrieval system, adaptively converting the knowledge content in the initial knowledge base by using the knowledge conversion rule model, outputting a converted knowledge base, and searching the real-time input modal of the permission user in the converted knowledge base to return a search result. The application solves the technical problems of low search efficiency and insufficient matching degree of the existing knowledge management based on information intelligent retrieval, and achieves the technical effect of improving the search matching degree and efficiency.

The present application discloses a data alarm analysis method and device, which includes: obtaining alarm information from a database at preset intervals; determining whether there are important keywords in the alarm information; if there are no important keywords in the alarm information, respectively calculating the similarity between the alarm information and the non-important keywords corresponding to each piece of knowledge in the knowledge base; determining each target knowledge from each piece of knowledge based on the similarity; wherein the similarity of the non-important keywords corresponding to the target knowledge is greater than a preset threshold; if there are important keywords in the alarm information; searching the knowledge base for each target knowledge with the same important keywords; and outputting access links corresponding to each target knowledge. Thus, instead of manually searching the knowledge base for content associated with the alarm information, the corresponding knowledge content is automatically searched from the knowledge base based on the keywords in the alarm information, thereby effectively improving the efficiency of the search.