97 results about "Knowledge content" patented technology

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 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 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 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 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 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 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 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 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.

The invention provides an EHS problem processing method, device and system. When the EHS problem is processed, a reference knowledge base meeting knowledge base requirements of the EHS problem initiated by a user is determined from the EHS knowledge base, the knowledge base requirements comprise knowledge content requirements, timeliness requirements and regional requirements, and reference knowledge of the EHS problem is retrieved in the reference knowledge base; the EHS knowledge base comprises an EHS stipulation class knowledge base, an EHS problem statistics class knowledge base and an EHS problem instance base. And then, on the basis of the EHS question and the reference knowledge, generating a cue word of a question and answer model realized on the basis of the large language model, and providing the cue word to the question and answer model to generate an answer to the EHS question. By means of the scheme, quick response to the EHS problem can be achieved, and therefore intelligent EHS management is achieved through the artificial intelligence technology.

The invention discloses a retrieval processing method and device for building an intelligent knowledge base based on AI and a terminal, and relates to the technical field of artificial intelligence. Selecting a knowledge base based on a large language model and a retrieval enhancement generation technology; inputting the document data subjected to format unification and classification into the knowledge base, creating intelligent agents of different posts, and constructing an intelligent knowledge base system; when a questioning question is received, performing agent intention recognition on the questioning question, and calling a corresponding post agent to search a knowledge base according to the recognized questioning intention; when the corresponding post agent does not find the answer in the knowledge base system, obtaining a reply answer, outputting the reply answer, and automatically writing the reply answer into the knowledge base for updating; and when the question answer is found, directly outputting the question answer. According to the method, rapid and accurate retrieval of enterprise internal knowledge can be realized, and missing knowledge contents can be automatically supplemented, so that the problems that employees are difficult to search systems, time is consumed and satisfactory answers cannot be obtained are solved.

The present disclosure relates to a water environment pollution analysis method, device and equipment based on a large language model, the method comprising: obtaining first information input by a user; determining a target knowledge segment from knowledge content related to a water environment according to the first information; generating a calling instruction for a target simulation model through a first large language model; obtaining a simulation result output by the target simulation model; and generating a target analysis result of a target water environment pollution event through a second large language model. With the above technical solution, through the dual mechanism of knowledge enhancement and tool enhancement, not only the accuracy and reliability of water environment pollution event analysis are improved, but also the target analysis result output by the second large language model has interpretability, providing effective guidance for environmental regulators to develop governance countermeasures.

This application provides a knowledge content recommendation and push method and related equipment. The method includes: acquiring user characteristics, including user data characteristics, content data characteristics, and background data characteristics; inputting the user characteristics into a knowledge content recommendation model to obtain a knowledge content recommendation table; and pushing knowledge content to the user based on the knowledge content recommendation table. The technical solution of this application, by inputting user-related data characteristics, content data characteristics, and background data characteristics together into a knowledge content recommendation model for comprehensive analysis, obtains knowledge content that better matches the user's interests and needs, forming a knowledge content recommendation table. Pushing knowledge content to the user based on this table can help users quickly find knowledge content of interest in an environment with a large amount of information, thereby reducing the time cost of information filtering.

1. Name of the product in this design: Graphical User Interface (Business Knowledge Guide) for Water Resources Business Analysis and Management System for Electronic Equipment. 2. Purpose of this design: An electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Uses of the graphical user interface: for building a learning system for project-related knowledge, evaluating work statistics, compiling and querying information on honors and awards, and assisting in work. 6. Human-computer interaction method of graphical user interface: Click "Knowledge Map" in the upper left corner of the main view to enter the interface change state diagram 1, which can view mind maps of various knowledge categories. Clicking "Add Knowledge Category" on the upper right of the interface change state diagram 1 will take you to the interface change state diagram 2. This interface allows you to add a root node. By entering information such as "Knowledge Title", "Sorting" and "Knowledge Content Type", you can add a new knowledge category. In the interface, "XXX" represents text, numbers, letters, or symbols.

The invention provides a traffic education information processing system. The system comprises a scene perception reasoning module, a dialogue driving module and a learning planning module. The scene perception reasoning module is used for acquiring scene information of the user, determining knowledge content corresponding to the scene information according to the scene information of the user and pushing the knowledge content to the user, and the scene information comprises a current position of the user, a current traffic environment and time information; the dialogue driving module is used for acquiring input information of a user and determining knowledge content corresponding to the input information and / or a presentation mode of the knowledge content according to the input information; the learning planning module is used for acquiring learning behavior information of the user and determining learning planning content corresponding to the learning behavior information according to the learning behavior information. Therefore, personalized requirements of the user are met, personalized traffic education content is provided, and learning effectiveness and interestingness are improved.

The invention discloses a knowledge recheck method, equipment, a storage medium and a device. Task execution parameters are configured based on an inspection mode corresponding to a knowledge reinspection task; calling a target inspection tool to execute inspection based on slice information and task execution parameters in a preset knowledge base, and obtaining an execution record; and performing problem positioning and slice tracing on the execution records to obtain knowledge optimization suggestions. Compared with the situation that real-time synchronization of knowledge and a valid system cannot be guaranteed through manual auditing, and the auditing efficiency is low, the method calls an inspection tool to execute inspection through slicing information and task execution parameters configured in a user-defined mode to achieve modular extraction and slicing of self-adaptive structured knowledge content, the data integrity is greatly improved, and the efficiency of the self-adaptive structured knowledge is improved. The inspection time is greatly shortened, and the inspection efficiency is improved.

The invention discloses a knowledge isolation method based on an organizational structure and user responsibilities. The method is composed of an isolation dimension management center, a multi-dimensional knowledge isolation method module and a knowledge production center. The isolation dimension management center transmits isolation strategies of organizations, tasks, identities and levels to the multi-dimensional knowledge isolation method module through a dimension configuration channel; the multi-dimensional knowledge isolation method module controls the access request according to a strategy through an isolation execution channel; and the knowledge production center outputs compliant knowledge content to the authorized user through the knowledge output channel. According to the method, refined and dynamic access control of the AI knowledge base in the enterprise is realized, and knowledge abuse is effectively prevented.

The invention provides a method for generating common law content. The method comprises the following steps: acquiring version information of laws and regulations; obtaining first text data; obtaining second text data; performing difference extraction on the first text data and the second text data to generate at least one difference feature; performing information identification on the difference characteristics to generate at least one key point label; based on the key point label, generating a corresponding description text through a first large language model; verifying the description text and the corresponding first text data, and judging whether the description text accurately reflects the first text data or not; if the verification is not passed, regenerating the description text until the verification is passed; and if the verification is passed, generating corresponding third text data based on the description text passing the verification. The method achieves the efficient and accurate generation of the general law content.

The invention relates to the technical field of computers, and provides an intelligent operation method and device for enterprise quality management, equipment and a medium, and the method comprises the steps: constructing a quality knowledge base based on multi-source quality data in an enterprise; receiving a quality task instruction from a user or an upstream system, and analyzing a task type corresponding to the quality task instruction and key parameters associated with the quality task instruction; calling a quality management workflow template based on the task type, the key parameters associated with the task type and a quality knowledge base, and generating a corresponding workflow; executing a corresponding task based on the workflow, and collecting feedback information related to task execution; and based on the feedback information, adjusting an analysis strategy for the quality task instruction and updating the knowledge content in the quality knowledge base. According to the scheme, intelligent closed loop of quality management is realized, and the problems of low efficiency, slow response, difficult data utilization, long improvement period and the like of a traditional mode are effectively solved.

The invention discloses a knowledge recommendation method, system and device based on multi-dimensional feature fusion and a medium. The method comprises the steps of obtaining user data and knowledge content data; extracting user features in the user data, and extracting knowledge content features in the knowledge content data; performing feature fusion on the user features and the knowledge content features to obtain a fused feature vector; calculating the similarity between the target user and other users to obtain knowledge contents liked by similar customers, and recommending the knowledge contents liked by the similar customers to the target user to obtain a first matching result; calculating the matching degree between the knowledge content to be recommended and the fusion feature vector to obtain a second matching result; and sorting the knowledge contents to be recommended according to the first matching result and the second matching result, and determining a final knowledge recommendation list according to a sorting result. The accuracy of knowledge recommendation can be improved.

The invention relates to the technical field of knowledge bases, can be applied to the field of science and technology finance / digital medical treatment, and discloses a knowledge base knowledge generation method and device, electronic equipment and a storage medium. The method comprises the steps that after knowledge generation process parameters configured by a user are obtained, the knowledge generation process is organized and managed in a unified mode, and the process parameters comprise knowledge data source types, knowledge generation structure requirements, knowledge generation rules and knowledge storage strategies. Collecting to-be-processed data based on the configured knowledge data source, processing the to-be-processed data under the constraint of the generation rule, and outputting structured knowledge content according to a preset structure; then manual auditing, intelligent auditing or combined auditing is executed according to the auditing configuration; after the audit is passed, the knowledge content is written into the target knowledge base according to a storage strategy, and vectorization processing is completed. According to the method, integrated automatic execution of knowledge generation regularization control, quality auditing and warehousing processing is realized.

The invention discloses a pipeline risk knowledge graph construction method based on generative causal flow, and relates to the field of pipeline risk knowledge graph construction. According to the method, the whole risk map is regarded as a time and space domain (t, x, y, z) generation process from nothing to thing, an event occurrence point is taken as an event starting point t0, and recognizable and observable time nodes of the whole event are divided into time nodes; then, association between space objects at the moment is mined on each time node ti, the space objects are related to all previous moments, parameters of the previous objects are related to the current object, and a time frame sequence sliced according to time is formed; and finally, hiding the time t, forming a spatially visual event object association graph only from the space (t, x, y, z), marking an event occurrence object as a risk point, and adding knowledge contents such as an event solution scheme, a specification, a requirement and the like according to a time sequence to form a pipeline risk knowledge graph.

The application relates to the technical field of computer information processing, in particular to a multi-modal video structured analysis and intelligent playing system and method based on a semantic time axis, aiming at the problems of insufficient video structured analysis capability, separation of playing and knowledge content, low processing efficiency and the like, a distributed asynchronous task architecture is constructed, audio and video preprocessing, speech recognition, time sequence semantic segmentation, subtitle generation and summary extraction are completed through a multi-modal analysis engine, and structured knowledge data accurately bound with a video time axis are generated. After automatic verification and manual review are completed through a quality control module, the structured knowledge base realizes associated storage of original videos and structured data and multi-dimensional index construction, and an intelligent interactive player realizes chapter navigation, subtitle synchronization and knowledge card linkage display in dependence on the semantic time axis. The application realizes standardized and structured conversion of unstructured videos, improves video processing efficiency and resource utilization, and reduces user knowledge acquisition cost.

The invention discloses an operation and maintenance strategy determination method based on a large language model and multi-agent cooperation, and relates to the field of artificial intelligence, the method comprises the following steps: analyzing an operation and maintenance request through the large language model to obtain target information; retrieving knowledge content related to the operation and maintenance request from an operation and maintenance knowledge graph to obtain summary information; determining N sub-tasks corresponding to the operation and maintenance request through the supervisor agent according to the target information and the summary information, and then distributing the N sub-tasks to Y target execution agents through the supervisor agent; processing the N subtasks through the Y target execution agents, and generating an operation and maintenance data set according to processing results of the N subtasks by utilizing the main agent; and generating an operation and maintenance strategy according to the operation and maintenance data set through the large language model. The technical problem that the efficiency is low when complex and unknown faults are processed due to the fact that an intelligent operation and maintenance system lacks effective multi-agent cooperation and large language model support in the prior art is solved.