121 results about "Knowledge level" patented technology

The invention provides a student adaptive auxiliary learning method and system based on artificial intelligence, and the method comprises the steps: constructing a subject knowledge graph, and carrying out the correlation and structuralization of knowledge points; the knowledge points are associated with learning resources and test questions in the subject knowledge graph; collecting learning behavior data of students, and constructing student portraits; the student portrait comprises three dimensions of learning style, knowledge level and hobbies and interests; wherein the knowledge level is a mastering probability of each knowledge point acquired according to the subject knowledge graph; personalized learning paths, learning resources and learning strategies are recommended to the students according to the student portraits and the subject knowledge maps; and learning results of the students are automatically evaluated and fed back. According to the characteristics and requirements of each student, a personalized learning scheme is provided, the learning efficiency is improved, the limitation of time and space is broken through, and the students can obtain high-quality learning resources which are more personalized for themselves anytime and anywhere.

The invention discloses a knowledge graph-based learning path design system, and belongs to the technical field of learning path design, and the knowledge graph-based learning path design system comprises a knowledge graph construction module which is used for collecting, sorting and representing knowledge in different fields from various sources, and constructing a knowledge graph model; the system comprises a learning module which is used for integrating knowledge levels, interests, preferences and learning style information of users into a coherent knowledge system, a user modeling module which is used for understanding and representing the knowledge levels, interests, preferences and learning style information of the users, and a learning path planning module which is used for generating personalized learning paths according to the information provided by the user modeling module. According to the method, multiple aspects of knowledge graph construction, user modeling, learning path planning, learning resource management, learning monitoring and the like are covered, and through cooperative work of the modules, the system can provide efficient, personalized and comprehensive learning path design, so that the experience and learning effect of learners are remarkably improved.

The invention discloses a virtual teaching training method and system based on a large language model and a medium, and the method comprises the following steps: determining preset feature parameters of virtual students according to teaching levels and subject contents; constructing a large language model, generating virtual students based on the large language model according to preset feature parameters of the virtual students, and inputting multi-modal teaching information; the virtual students perform model training and learning on the multi-modal teaching information to generate learning state information and feedback information; the virtual teaching expert proposes a suggestion for dynamically adjusting and optimizing the teaching strategy based on the evaluation result; dynamic learning and interactive feedback are carried out by simulating virtual students with different priori knowledge levels and cognitive competence, and meanwhile, real-time evaluation and personalized improvement suggestions are carried out on the teaching process by utilizing the constructed virtual expert system, so that a user is helped to continuously optimize a teaching strategy, and the teaching quality of a specific subject is improved.

The invention belongs to the field of examination systems, and particularly relates to an online examination automatic test paper composition method based on a knowledge graph, and the method comprises the following steps: S1, data collection; s2, constructing an atlas; s3, collecting and analyzing examinee information; s4, analyzing examination requirements; s5, formulating a test paper generation strategy; and S6, test paper generation and verification. According to the online examination automatic test paper composition method based on the knowledge graph, knowledge materials are widely collected through multiple channels, data mining and semantic network technologies are used for carefully analyzing knowledge point relations, and the constructed knowledge graph is distinct in hierarchy and rich in semantics. And formulating a strategy by using an intelligent algorithm according to knowledge level evaluation and examination requirements of examinees during paper composition. For weak or important examination knowledge points of examinees, the number of questions, score weights and difficulty levels can be accurately controlled, blindness of traditional test paper composition is avoided, test paper is made to closely fit the reality of the examinees, and the knowledge mastering and application ability of the examinees is accurately evaluated.

The invention provides an expert knowledge-driven large-model customized data processing method and related equipment. The method comprises the following steps: inputting acquired business data into a trained large model capable of dynamically customizing an expert sub-model; in the large model, based on the business data, determining a knowledge embedding vector; based on the knowledge embedding vector, determining the weight of each adapter expert, and customizing an expert sub-model; and processing the business data based on the expert sub-model. According to the embodiment of the invention, the business knowledge hierarchical structure is constructed by using the multi-dimensional business information and the expert knowledge based on the large-scale business data. In combination with a large-model efficient fine tuning technology and a mixed expert strategy, dynamic expert group adaptation is realized under the guidance of business data knowledge, so that different expert models are customized for different business data, automatic adaptation under multiple scenes is realized, and more professional data processing is realized.

The invention relates to the technical field of intelligent retrieval, in particular to an engineering knowledge base construction and deep retrieval method, which comprises the following steps of: in a knowledge base construction stage, performing knowledge level identification on an engineering knowledge document to form a multi-level tree structure taking chapter titles and corresponding contents as nodes; performing analysis processing on the heterogeneous content of each node to generate knowledge fragments; and generating embedded vectors of knowledge fragments by adopting a way of combining path embedding and content embedding, and storing association relationships among knowledge, vector data and original information to complete knowledge base construction. In the deep retrieval stage, after a user question is received, a knowledge blank question list is generated through query and rewriting, a knowledge base is retrieved through traversal of the list, the retrieval process is optimized through knowledge grouping, correlation sorting and loop termination judgment, and finally reply content subjected to traceable verification is generated and output based on existing knowledge accumulated in a circulation mode. According to the method, the reuse efficiency and the retrieval accuracy of the engineering knowledge can be improved.

The invention discloses a junior high school English reading understanding intelligent proposition method based on an education large model. The method comprises the following steps: S1, identifying a proposition thought and a common proposition method of a proposition person; s2, generating a propositional strategy knowledge base; s3, obtaining a text material of junior high school English reading understanding, and performing preprocessing operation; s4, determining difficulty distribution of the reading material on different knowledge dimensions; s5, performing grading processing on the content of the question according to different difficulty dimensions; s6, content details and difficulty progressive levels of the questions are refined through a spatial fractal algorithm; s7, generating a multi-dimensional evaluation result of the knowledge level of the student; and S8, according to the multi-dimensional evaluation result and the learning track of the student, the system optimizes and adjusts the next generated question through an education large model in combination with a fuzzy topology and spatial fractal algorithm. According to the invention, while learning requirements of different students are met, the question generation quality and the teaching effect are significantly improved.

The invention discloses a learning path recommendation method fusing a hierarchical knowledge graph and deep knowledge tracking, and belongs to the technical field of data analysis, and the method comprises the following steps: constructing a KGDKT model, and constructing a deep knowledge tracking model capable of considering a logic relationship between knowledge points; searching a learning path, and generating all paths pointing from the starting point knowledge point to the target knowledge point based on the hierarchical course knowledge graph and the KGDKT; and optimal path selection: predicting the mastering degrees of the target knowledge points of the learner on different paths through KGDKT, and selecting one path with the best learning effect to be recommended to the learner. The path generated by the method accords with the logical relationship between the knowledge points, can adapt to the dynamically changing knowledge level of the learner, and improves the learning effect of the learner on the target knowledge point.

The invention discloses a knowledge learning management method and device based on data analysis, and the method comprises the steps: obtaining a scene behavior data set, the scene behavior data set comprises the behavior data of each pharmacy employee in different business scenes, and the business scenes at least comprise a drug recommendation scene, a drug taboo reminding scene and a special medication consultation scene; constructing a behavior model according to the scenarized behavior data set, and extracting behavior feature information of the drugstore employees in different business scenes through the behavior model; determining a knowledge point set and a knowledge blind area which need to be mastered by the drugstore employee in each business scene based on the behavior feature information; constructing a knowledge graph according to the scenarized behavior data set, the knowledge blind area, the knowledge point set and the association relationship between the knowledge point set and the business scene; and based on the knowledge graph, determining professional learning contents of the drugstore employees and priorities corresponding to the professional learning contents. The professional knowledge level of drugstore employees can be comprehensively improved.

The invention discloses a micro course generation method based on OCR recognition and a server, and relates to the field of image data processing, and the method comprises the steps: collecting maintenance record document image data, and carrying out the optical character recognition processing of the maintenance record document image data, and obtaining digital text data; performing natural language processing on the digital text data according to a preset bidirectional encoder representation model, and integrating the terminology information, the fault code information and the operation step information into structured knowledge data; obtaining a knowledge level parameter and a post information parameter of the target user, and performing difficulty grading on the structured knowledge data according to the knowledge level parameter to obtain difficulty grading knowledge data; performing knowledge range screening in the difficulty grading knowledge data according to the post information parameters to obtain target knowledge data; and selecting teaching materials matched with the target knowledge data from the knowledge resource library, and generating a micro course resource bundle according to the teaching materials. By implementing the method, the updating efficiency of the training data can be improved.

The invention discloses a resource learning path planning method and device based on deep learning, and the method comprises the steps: obtaining the knowledge levels and historical record information of a plurality of learners, building a learner model according to the historical record information and the knowledge levels, calculating the learner similarity between any two different learners in the learner model, and obtaining the learning path of the learners. Constructing a learning behavior model corresponding to the learner according to the learner similarity, predicting the cognitive level of the learner according to the learning behavior model and the learner model, constructing a learning path recommendation model according to the cognitive level, and planning a target learning path corresponding to the learner according to the learning path recommendation model and a preset knowledge graph, the learning behavior indexes are quantified according to the learning behaviors of the learner to construct the learner model, the learning path is recommended to the learner, the knowledge graph is combined to further complete accurate learning path planning, and a practical, reasonable and explainable learning path is provided for the learner, so that the learning efficiency and quality of the learner are improved.

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

The invention relates to the technical field of artificial intelligence, and discloses a marketing knowledge base construction method, device and equipment based on artificial intelligence, and the method comprises the steps: obtaining basic information and session information, and converting the session information into text data according to the basic information; analyzing implicit relation data among the employees, the products and the clients based on the basic information, and extracting marketing knowledge from the text data; and carrying out hierarchical classified storage on the implicit relation data and the marketing knowledge, and pasting multi-dimensional labels on different knowledge to form a marketing knowledge base. According to the invention, through integration and structured processing of multi-source data, potential association among employees, products and clients is mined, and actual marketing knowledge is accurately extracted; hierarchical storage enables a knowledge system to be clearer, and multi-dimensional labels improve retrieval efficiency; the dynamic updating mechanism ensures the timeliness of knowledge, provides accurate knowledge support for a marketing scene, assists employees to quickly match verbal skills and schemes, and improves the communication efficiency and the transaction rate.

The invention discloses a personalized tutoring method integrating collaborative cognitive diagnosis and adaptive teaching. The method comprises the following steps: firstly, constructing a college entrance examination data set, constructing an initial knowledge hierarchy tree of each college entrance examination subject according to the college entrance examination data set, and sequentially performing cognitive diagnosis processing on knowledge points corresponding to unmarked nodes on the knowledge hierarchy tree according to the initial knowledge hierarchy tree in an inverse sequence traversal sequence to obtain an initial student cognitive state tree; the teacher performs tutoring processing on all the sub-question-solving steps of each college entrance examination question according to the initial student cognitive state tree until tutoring processing on all the sub-question-solving steps is completed; and all college entrance examination questions are tutored in a repeated traversal manner until all college entrance examination questions are tutored. According to the method, through two-stage personalized tutoring of cognitive diagnosis and adaptive teaching, accurate evaluation of student individual cognitive states and adaptive adjustment of teaching strategies are realized, and the performance of the method is superior to that of an existing method.

The invention discloses an aircraft fly-by-wire teaching simulation system, which comprises a flight operation table, a simulation computer and a comprehensive display system, the flight operation platform is in communication connection with the simulation computer; and the comprehensive display system is electrically connected with the simulation computer, and the comprehensive display system is used for displaying teaching contents of the fly-by-wire control system of the airplane, virtual flight scenes and virtual cabin instruments. A virtual reality technology is adopted, and technical means such as computer simulation and system modeling are comprehensively adopted, so that flight trainees can more intuitively understand theoretical knowledge such as basic composition, working principle, control rate calculation and control instruction response of an aircraft telex system, and the aircraft telex system can be simulated through control simulation training. Feedback of each functional module of the aircraft telex system to an aircraft control instruction is sensed in an immersive manner, the telex system theoretical knowledge level of a pilot can be improved, meanwhile, the actual installation loss is reduced, and economy and safety are achieved.

The invention discloses a building safety education training system based on interactive experience, relates to the technical field of construction site safety education, and aims to solve the problems that traditional building worker safety education lacks pertinence and is difficult to meet specific safety requirements of various types of work, and the teaching mode is relatively single. The system comprises a database, a personalized learning recommendation module, an interactive learning module and a learning progress and achievement tracking module. The database is used for pre-storing safety knowledge of various construction work types; the personalized learning recommendation module is used for screening and recommending learning content suitable for the worker from a pre-stored database covering safety knowledge of various construction work types according to the work type information and learning history of the construction worker, and the learning content comprises a document and a video course. The method has the advantages that precise education content conforming to the work type and the knowledge level of each worker is provided for the worker, and the safety awareness and the skill level of the building worker are improved.

An object of the system according to the embodiment is to provide a summary according to a knowledge level of a reader and optimize a reading experience.SOLUTION: A system according to an embodiment includes a summary generation unit, a marker function unit, a summary generation unit, and an expression change unit. The summary generation part generates a summary corresponding to the knowledge level of the reader. The marker function unit adds a marker to a specific range of the summary generated by the summary generation unit. The summary generation unit generates a summary of the range marked by the marker function unit. The expression changing unit changes an unclear part of the summary generated by the summary generating unit to a simple expression.SELECTED DRAWING: Figure 1

The invention provides an industrial process zero sample fault diagnosis method based on a similarity consistency relation, and relates to the technical field of fault diagnosis and classification. From the perspective of similarity between faults, on one hand, understanding of experts on the faults is deeply mined, and the similarity between fault categories is constructed based on the knowledge level; and on the other hand, the model is trained by using the known fault data, the data features of the known faults are extracted on the data level, and the similarity between the fault features is quantified from multiple angles. By solving a group of consistency parameters, mapping of faults from knowledge similarity to data similarity is constructed. Through the mapping, the abstract and comprehensive similarity relation of the knowledge level can be specifically explained by utilizing the similarity measurement of the data level, and the diagnosis of unseen class faults can be effectively supported.

Augmenting a live broadcast of a sporting event includes receiving or generating a data stream of a live broadcast of a sporting event, generating commentary on the live broadcast in real time at a plurality of different levels of knowledge of the sport of the sporting event being broadcast, determining a knowledge level of the sport of a user, and providing the generated commentary at one of the plurality levels of knowledge of the sport to a user in real time based on the determined knowledge level of the sport of the user.

The invention discloses a Transform-based student side information fusion knowledge tracking method, which comprises the following steps of: constructing a sequence-to-sequence model, and separating a learning record sequence of a student into an exercise sequence and an answer sequence; embedding the obtained sequence into side information to obtain an exercise and answer embedding sequence; a Transformer model based on an attention masking mechanism is constructed, an exercise embedding sequence is input into an encoder, the encoder captures the relation between exercises through a multi-head attention mechanism, then nonlinear features are added to obtain output # imgabs0 #, a decoder combines an answer embedding sequence with the output # imgabs1 # through the multi-head attention mechanism and captures the relation between exercises and answers, and the answer embedding sequence and the output # imgabs1 # are combined through the multi-head attention mechanism. Adding nonlinear features to obtain decoder output; and generating a prediction probability of the student to do exercises. According to the invention, the knowledge level of the student is constructed more comprehensively, and the accuracy of predicting the knowledge state of the student is improved.

The invention relates to the technical field of industrial automation and intelligent control, in particular to a multi-mode data and knowledge driven industrial process control core component, which comprises a multi-mode data interface and a preprocessing unit, the system and the method have the advantages that multi-modal sensing data and domain knowledge are deeply fused, accordingly, comprehensive and three-dimensional perception of industrial process states can be realized, data analysis can be guided and constrained by the aid of the knowledge, and the system and the method can be applied to the industrial process states. Therefore, the accuracy and robustness of the control decision are remarkably improved, and the data-driven decision result has the interpretability of the knowledge level by constructing a bidirectional fusion channel of the data and the knowledge, so that the trust problem of a black box model is solved.

The invention provides an educational question and answer method based on a multi-modal knowledge graph and multiple agents and a related device, and belongs to the technical field of educational question and answer. The method comprises the following steps: generating initial education question and answer content based on an obtained cognitive portrait of a learner and multi-modal knowledge data matched with a question and answer request in a multi-modal knowledge graph, and verifying the initial education question and answer content to obtain a verification result; judging whether the verification result meets the requirement or not, and if the verification result meets the requirement, collecting feedback data of the learner about the initial education question and answer content; based on feedback data of the learner about the initial education question and answer content, the multi-modal knowledge graph and the question and answer service process are adjusted through multiple agents. According to the method, the problems that a personalized adaptation mechanism for learners in different subjects, knowledge levels and professional directions in the education field is lacked, and high-quality question and answer service of an education scene is difficult to support are solved.

The present application relates to the technical field of knowledge tracking, and relates to a method for dynamically evaluating student knowledge level based on a double attention mechanism, comprising the following steps: S1. obtaining interactive information of a student learning process, and grouping the interactive information into a sequence; S2. dividing the interactive sequence into three parts, namely a dynamic problem level sequence, an average skill level sequence and an additional feature sequence; S3. inputting different sequences into corresponding modules for training, and obtaining a student knowledge state through a long short-term memory network and multiple attention mechanisms; S4. inputting the knowledge state into an interpretability module to evaluate the knowledge level; and S5. recording training model evaluation indexes, verifying the interactive sequence of the student through a model updated by parameters, and evaluating the knowledge level of the student. The present application fully mines the interactive information of the student, evaluates the knowledge state of the student from different angles, and improves the accuracy of predicting the future performance of the student.

The present invention discloses a big data learning analysis method for panoramic scanning of learning situation, including: collecting students' learning situation panoramic data and preprocessing them to obtain preprocessed learning situation panoramic data; vectorizing the preprocessed learning situation panoramic data to obtain a learning situation panoramic vector sequence; constructing a knowledge state evaluation model, inputting the learning situation panoramic vector sequence into the model, and outputting the students' knowledge level state; constructing a personalized learning resource recommendation model, and matching learning resources based on the similarity matching analysis between the students' knowledge level state and different learning resource data. The present invention constructs a learning situation panoramic vector sequence that characterizes the changes in students' knowledge points during the learning process, evaluates the students' current knowledge level state, and realizes personalized and accurate recommendation of learning resources based on the overlap between the weaknesses of the knowledge level state and the knowledge points contained in the learning resources.

A data processing device includes: a processor, in which the processor is configured to collect input information from a specific user, the input information being related to a specific technology, specify, by using a generation model, a knowledge level of the specific user for the specific technology based on the collected input information from the specific user, generate, when information related to the specific technology is requested from the specific user, technical information for the specific user based on the requested information related to the specific technology and the knowledge level of the specific user for the specific technology by using the generation model, and output the technical information for the specific user to the specific user.

To reduce an on-site burden due to a shortage of educational resources of a mid-career employee.SOLUTION: Provided is a system for assisting education of a just joined member with little knowledge, including: means for collectively presenting related keywords and examples proposed by other sales members based on an input keyword on an inexplicit knowledge level; and means in which a generative AI functions as an educator for reducing educational resources of a mid-career employee.SELECTED DRAWING: Figure 1

The invention discloses a medical imaging teaching assistance method and system based on AI, and the method comprises the steps: collecting the learning background information of all students, and evaluating the knowledge level of the students; according to the knowledge level evaluation result of the student, intelligently planning course content; evaluating the mastering degree of the students on the course knowledge points to realize the dynamic adjustment of the teaching content; inputting the student data into an AI-based learning condition evaluation model, and optimizing the teaching content and method by the teacher according to the course learning condition of the student fed back by the model; a teaching resource sharing platform is established, different specialized teachers share teaching resources and information, teaching content communication is achieved, the real-time learning degree of the students on courses is known based on an AI learning condition evaluation model, the teachers dynamically adjust the teaching content, the teaching flexibility and adaptability are improved, and the learning effect of the students is improved.

The application relates to a wisdom detection system, method, equipment and medium based on robot technology, wherein the method comprises the following steps: an advanced detection module is used for acquiring detection data of a target robot according to a target detection element, so that the target robot performs a preset detection operation; a remote transmission module is used for acquiring environment information corresponding to the target robot according to real-time positioning information of the target robot, so as to determine a corresponding data transmission mode to transmit the detection data; a data wisdom management module is used for performing data processing and evaluation operation on the detection data, so as to obtain standard detection data, and based on a deep learning model, an adverse geological body identification result corresponding to the standard detection data is acquired. Therefore, the problems that the interpretation and evaluation process of the prior art excessively depends on professional knowledge level and engineering experience, the initial geophysical prospecting error is large, the adverse geological body is difficult to verify through drilling, and the stability of the detection element and the detection effect are greatly affected are solved.

To provide an information processing apparatus, a method for information processing, and an information processing program for easily providing information according to IT knowledge.SOLUTION: The present invention stores management information that has been managed related to system development, selects a knowledge level in system development, provides, to a user, a consultation input screen for entering consultation matters related to system development in accordance with the selected knowledge level, searches stored management information on the basis of the consultation matters entered in the consultation input screen and acquires search results, obtains, from a large language model, an answer generated in response to a prompt including at least the consultation matters entered in the consultation input screen and the acquired search results, and provides the obtained answer.SELECTED DRAWING: Figure 1

The invention discloses a resident energy-saving effect evolution prediction method and system, and the method comprises the steps: obtaining user preferences, user energy-saving knowledge levels and user education levels in a resident community, obtaining the number of household electric appliances of a user, and obtaining the data of a power transmission line in the resident community; on the basis of an entropy weight method, entropy values of user preferences, user energy-saving knowledge levels, user education levels and user household electric appliance numbers are calculated, and user load data are obtained through calculation according to the entropy values; performing transformation processing on the user load data and the power transmission line data based on Fourier transform, and analyzing correlation characteristics between the user load data and the power transmission line data to obtain a load correlation factor and a power transmission line correlation factor; and performing association prediction analysis on the user load data based on the load association factor and the power transmission line association factor to obtain load characteristic data. According to the resident energy-saving effect evolution prediction method provided by the embodiment of the invention, accurate detection of load prediction is realized.