150 results about "Knowledge content" patented technology

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 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 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 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 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 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.

The invention discloses an automatic extraction and query system for power grid standard knowledge, and the system comprises the following modules: a knowledge segmentation module which is used for segmenting the power grid standard knowledge into a plurality of knowledge blocks; the entity extraction module is used for extracting entities contained in the knowledge blocks and entity information of the entities; the feature extraction module is used for extracting features of the document blocks and the entity information by using an LLM-based Encoder network structure; the database module is used for storing knowledge contents and features thereof and providing retrieval capability based on vector similarity; the user question processing module is used for preprocessing questions of the user so as to carry out matching retrieval; the matching retrieval module is used for carrying out matching according to the query content and the knowledge content, and a plurality of matching paths exist; and the reordering module is used for reordering the multiple paths of matching results to obtain a final ranking, and the ranking is a query result. According to the invention, efficient extraction and retrieval of power grid standard knowledge are realized.

The invention provides a marketing knowledge base construction system and method based on a large model, and the method comprises the steps: firstly determining a knowledge construction demand in an automobile marketing field, generating a marketing knowledge demand description, inputting the marketing knowledge demand description into a pre-training large model to generate candidate knowledge contents, and then carrying out the evaluation of the candidate knowledge contents according to a preset knowledge quality evaluation standard, the method comprises the steps of generating an evaluation result, inputting marketing knowledge demand description, candidate knowledge content and the evaluation result into a large model for instruction fine tuning to obtain optimized knowledge content, and finally performing structured organization on the optimized knowledge content to generate an automobile marketing knowledge unit and adding the automobile marketing knowledge unit to a knowledge base. Therefore, the construction efficiency and quality of the automobile marketing knowledge base can be effectively improved, and a systematic, accurate and practical knowledge base is provided for automobile marketing.

The invention discloses an automatic bidding and tendering knowledge collection method and system based on semantic analysis and a storage medium, and relates to the technical field of digital bid evaluation. Establishing a professional database in the bidding and tendering field, and constructing a bidding and tendering knowledge graph based on association relationships of various knowledge in the professional database; obtaining a to-be-collected bidding and tendering text, preprocessing the to-be-collected bidding and tendering text, inputting the to-be-collected bidding and tendering text into the trained NLP semantic classification model, performing semantic segmentation on the bidding and tendering text, and identifying domain entities, attributes, relationships and theme information in the text; generating a corresponding semantic classification label according to the semantic analysis result; and inputting the semantic classification labels into the tendering and bidding knowledge graph, automatically extracting knowledge contents in the text in combination with the semantic classification labels, and classifying the knowledge contents into corresponding knowledge modules to complete automatic collection of knowledge. According to the method, the problems of low efficiency, poor accuracy and low standardization of current bidding and tendering knowledge collection are solved, and efficient and accurate support is provided for knowledge management.

The embodiment of the invention provides a retrieval method and a computer program product, and the method comprises the steps: obtaining to-be-retrieved information, and matching the to-be-retrieved information with a sub-fragment window dictionary based on a trained retrieval model when the to-be-retrieved information meets a preset condition, the sub-fragment window dictionary comprises each sub-fragment window and a feature vector corresponding to each sub-fragment window, obtaining a combined word matched with the retrieval information from the sub-fragment window dictionary, determining a feature vector corresponding to the combined word, obtaining a knowledge fragment corresponding to the to-be-retrieved information based on the to-be-retrieved information and the feature vector corresponding to the combined word, and storing the knowledge fragment in the sub-fragment window dictionary. Key knowledge content can be focused, vector information out-of-focus is avoided, and then retrieval precision is improved.

The invention provides a normal school student teaching ability evaluation method based on a affair knowledge graph fused with a big language model. The method comprises the following steps: S1, acquiring graphic and text information of teaching content and video information of a target object; s2, extracting knowledge content from the graphic and text information, and constructing a subject knowledge graph according to the knowledge content; s3, according to the video information and the subject knowledge graph, event elements in the video information are extracted, and event coding data are obtained; s4, constructing a affair knowledge graph based on the event coding data; s5, calculating a teaching ability score of the target object according to the event coding data; and obtaining personalized ability evaluation feedback of the target object based on ability interpretation of the large language model. According to the method, the behavior data and the image-text data of the target object are collected, and the teaching behavior and the knowledge framework in the teaching process of the normal school students are used as characterization of the teaching ability of the normal school students, so that the teaching ability can be evaluated more comprehensively and accurately.

The invention discloses an automatic reply method, device and equipment for media content comments, a medium and a product, and relates to the technical field of intelligent questions and answers. The method comprises the following steps: receiving media content sent by a media content publishing end, a media account corresponding to the media content, a comment to be replied in the media content and a context of the comment to be replied; based on the to-be-replied comments, obtaining knowledge contents related to the to-be-replied comments from a knowledge base; based on the media account, selecting a target comment reply model corresponding to the media account from a plurality of pre-trained comment reply models; taking the media content, the comment to be replied in the media content, the context of the comment to be replied and the knowledge content related to the comment to be replied as input of a target comment reply model, and outputting a comment reply corresponding to the comment to be replied; and finally, the comment reply is sent to the media content publishing end. According to the method, the comments can be replied in time, and the interaction effect with the user comments is enhanced.

The invention relates to an intelligent reading recommendation method and system based on dynamic learning ability evaluation, and relates to the field of intelligent education technology.The method comprises the steps that current scanning content is extracted based on scanning behavior data, knowledge content mastered by a user is recognized in combination with historical learning records, and the knowledge content is removed to obtain an unmastered knowledge range; analyzing the current scanning content to identify knowledge entries and evaluating the learning difficulty of the entries; based on historical learning records and knowledge entries, evaluating expected time required for understanding the current scanned content; determining an actual understanding time based on the scanning behavior data; the real-time learning ability of the user is generated in combination with the actual understanding time, the expected time and the entry learning difficulty; and generating learning recommendation content based on the real-time learning ability and the unmastered knowledge range, and performing content recommendation based on the learning recommendation content. The method has the effect of improving the learning efficiency and experience of the user.

The invention relates to the field of multi-modal modeling, and provides a three-dimensional enterprise knowledge base construction method and system. The method comprises the following steps: classifying and marking knowledge assets to be constructed according to a preset dimension system, and extracting semantic feature information corresponding to multiple dimension knowledge nodes to obtain a multi-dimensional cross knowledge framework; knowledge nodes in the multi-dimensional cross knowledge framework are stored in a graph database, a knowledge association network is established, and a dynamic knowledge graph is obtained; collecting user feature data, and generating a user knowledge demand portrait according to the user feature data; performing matching calculation on the user knowledge demand portrait and knowledge nodes in the dynamic knowledge graph, and screening matching results to obtain a target knowledge push list; and determining an access permission level according to the role permission attribute of the user, performing permission verification on the knowledge nodes in the target knowledge pushing list based on the access permission level, and generating personalized knowledge content. According to the invention, the knowledge management efficiency, the delivery accuracy and the security are improved.

The invention discloses a root tracing method and device for knowledge content, equipment and a readable storage medium. The method comprises the following steps: positioning at least one piece of difference information from target answer content uploaded by a target user; the root cause classification of each piece of difference information is determined, the root cause classification is the error type to which the information corresponding to the point losing point belongs, and the error type comprises information known and information unknown; and / or the error type comprises information missing and information redundancy; the root cause tracing result of the difference information under the error type is determined through the large language model, and the root cause tracing result of the difference information can be displayed to the user, so that the user can perform improvement based on the root cause tracing result of the difference information, and the analysis ability of the user is helped to be improved.