105 results about "Basic knowledge" patented technology

The invention discloses a learning content determination method and device based on an intelligent education platform and electronic equipment, and relates to the technical field of data processing, and the method comprises the steps: extracting a basic knowledge point cluster and a key knowledge point cluster from a student teaching material, and generating a target question bank containing different difficulties and question types; generating a knowledge point association network according to the association relationship and strength of the knowledge points corresponding to the questions in the target question bank; and in combination with the learning track of the student in the learning map, generating the target association strength between the target knowledge points, updating the knowledge point association network according to the target association strength, obtaining a student exclusive target association network, and updating the target question bank to determine the target learning content of the user. According to the scheme, the knowledge points are extracted through the textbook, the target question bank of the multivariate question types is generated, the problem of single question type in the prior art is solved, the question bank is dynamically updated in combination with the learning track and the association network, students can focus on core knowledge points, and the learning efficiency is improved.

The invention belongs to the technical field of education course recommendation, and discloses a personalized learning path recommendation method based on a knowledge graph, which comprises the following steps: acquiring a knowledge point set according to a learning target, and constructing a basic knowledge graph; matching the first similar group, and obtaining learning records of the first similar group to form a first reference record set; marking difficulty values for the knowledge points according to the mastery degree in the first reference record set, and generating a knowledge point learning sequence; taking the first reference record set as a target reference set, and matching an optimal learning track for each knowledge point to obtain a comprehensive learning path; after learning records of the learner are obtained, matching a second similar group, and obtaining a second reference record set; and optimizing the comprehensive learning path according to the second reference record set, and adding review nodes for the knowledge points with low mastery degree. According to the method, knowledge point difficulty values are marked based on actual learning data, a learning sequence of cognitive load balance is generated, a dynamic recommendation process from general to individuation is realized, and learning efficiency and experience are improved.

The invention discloses a teaching optimization method, system and device based on knowledge space and a medium. The method specifically comprises the steps that a secondary node platform is analyzed based on national industrial internet identification, official teaching materials are analyzed to generate knowledge point entities with identification codes, and a relation network is established; based on the relational network, collecting a multi-platform question bank problem solving step, performing authentication in combination with an identification code matching mechanism, synchronizing to a basic knowledge space after authentication, marking as an extended knowledge point library, and calculating a difficulty threshold value of a knowledge point association combination in combination with wrong question statistics; and on the basis of the relational network, cross-platform problem solving steps of the learner are captured in real time, authentication is carried out in combination with an identification code matching mechanism, if authentication is not passed, a preposed knowledge point unmastered state is marked, and a learner problem solving knowledge space with a state mark is generated. According to the invention, comprehensive analysis of the knowledge point mastering condition of the learner, difficult point positioning and personalized teaching optimization suggestion generation are realized, and the teaching quality and the learning effect are improved.

The invention provides a retrieval enhancement generation method and a retrieval enhancement generation system. The retrieval enhancement generation method comprises the following steps: segmenting basic knowledge text segments and carrying out semantic vectorization processing; establishing a historical relation graph; carrying out vectorization processing on nodes of the historical relation graph; obtaining a direct query result vector and a corresponding direct matching degree according to user query content; obtaining similar historical query vectors and corresponding similar historical query result vectors according to user query contents; calculating a historical matching degree through the direct query result vector and the similar historical query result vector; and calculating the overall matching degree, reordering the direct query result vectors, and then generating cue words and inputting the cue words into the large model. According to the technical scheme, the similarity analysis can be performed on the historical query result confirmed by the user and the direct query result, and the direct query result is reordered, so that the target query result which is more accurate and better meets the user requirement is obtained.

The invention provides a dynamic updating method and system of a knowledge graph based on reasoning enhancement. The method belongs to the cross technical field of artificial intelligence, knowledge engineering and dynamic system modeling. The method comprises the following steps: performing multi-dimensional feature extraction on original knowledge data to generate a knowledge feature vector set; constructing an initial knowledge graph structure based on the knowledge feature vector set, and defining an initial association rule between knowledge nodes to form a basic knowledge graph model; building a multi-order causal inference engine according to the basic knowledge graph model, performing deep mining on potential causal relationships among knowledge nodes, and generating a knowledge causal relationship network; and performing confidence evaluation on each causal chain in the knowledge causal relationship network to obtain the knowledge causal relationship network subjected to quality verification. Based on a multi-order causal reasoning engine, the system can mine and verify potential causal relationships among knowledge nodes in real time, and continuous updating and self-optimization of the knowledge graph are ensured.

The invention discloses a method and a system for generating a manufacturing process disturbance knowledge graph, and a storage medium. The method comprises the following steps: constructing a mode layer of the knowledge graph; inputting the SMT manufacturing process disturbance data set into the trained entity recognition model for processing to obtain an entity in the SMT manufacturing process disturbance data set; extracting the context of the entity to obtain an attribute corresponding to the entity and a relationship between the entities; fusing entities in the SMT manufacturing process disturbance data set, attributes corresponding to the entities and relationships between the entities based on the mode layer, and constructing a first SMT manufacturing process disturbance knowledge graph based on a Neo4j database; performing relation completion and attribute completion on the SMT manufacturing process disturbance basic knowledge graph to obtain a final SMT manufacturing process disturbance knowledge graph; according to the method for generating the disturbance knowledge graph in the manufacturing process, system modeling and efficient utilization of bad process knowledge are realized.

The invention relates to a superconducting power knowledge system construction method and system based on a lightweight large model. According to the method, multi-source data is utilized for unified representation, deep semantic information is obtained through a lightweight large model, knowledge extraction is achieved, and a basic knowledge graph is constructed; further forming a knowledge graph which can be dynamically updated through knowledge fusion; and in combination with real-time data, adaptive multi-hop reasoning is executed, and a diagnosis and decision result with a causal chain is generated. According to the method, the semantic understanding and reasoning ability of a lightweight large model is taken as a core, the structural expression advantage of a knowledge graph is combined, the limitation of updating lagging and fixed rule reasoning rigidness of a traditional static knowledge base is broken through, and precise cognition and causal chain inference of a complex system state are achieved. The method has universality and mobility, and is suitable for knowledge modeling and intelligent diagnosis of various electric power scenes and other complex industrial systems. The method is verified by taking a superconducting power system as an example, and the feasibility and effectiveness of the construction path are proved.

The invention provides a ground vibration spectrum acceleration prediction method, a transfer learning method, equipment and a medium, a global model is obtained through first training by using a basic knowledge data set, the first training is evaluated by using a regional knowledge data set, and then a transfer model is obtained through second training by using the regional knowledge data set. And the second training is evaluated by adopting the regional knowledge data set, and the establishment method of the migration model retains the data features of the regional database and learns the difference between the global data set and the regional data set, so that the prediction precision of the model is ensured, and the generalization ability of the model is enhanced.

The invention discloses a dynamic hierarchical knowledge graph construction method and system for an operator test, and mainly relates to the technical field of educational information. Comprising the following steps that a three-layer knowledge graph is constructed, the three-layer knowledge graph comprises a basic knowledge point layer, a question type rule layer and a current political examination point layer, and each layer comprises a plurality of entities, entity attributes, intra-layer association relationships and cross-layer association relationships; s2, updating the three-layer knowledge graph in the step S1 through a dynamic iteration mechanism: acquiring data from a data source, automatically extracting entities and relationships, triggering graph updating and performing conflict verification; based on post information input by a user, post characteristics are analyzed, weights of test points are calculated, and a post exclusive knowledge graph is generated according to the weights. The beneficial effects of the invention are that the system achieves the dynamic updating of the examination knowledge of the public operator, achieves the hierarchical management, achieves the precise matching of positions, and remarkably improves the examination preparation efficiency and pertinence.

The invention relates to the field of artificial intelligence, machine learning and data mining, and discloses a user behavior information intelligent analysis method based on a knowledge graph, and the method comprises the following steps: (1) carrying out the preprocessing of multi-source user behavior data, and generating a materialized behavior sequence; (2) constructing a domain basic knowledge graph; (3) performing incremental expansion on the knowledge graph according to the real-time behavior data to generate a user personalized sub-graph; (4) carrying out dynamic updating and pruning on the personalized subgraph; (5) fusing multi-user sub-graph knowledge through a federal learning framework; and (6) providing an intelligent analysis interface based on the updated knowledge graph. According to the method, real-time semantic modeling of user behaviors is realized through incremental expansion and causal verification, and the analysis precision and timeliness are improved; and in combination with federal fusion and map path reasoning, traceable decision support is provided under privacy protection, and the service credibility is enhanced.

The invention discloses an AI-based modern apprentice system personalized teaching system and method for medical students. Firstly, multi-dimensional data collection is carried out, and an initial data set is constructed by covering theoretical and practical scores, learning preference styles and the like; analyzing data by using an AI algorithm combining an analytic hierarchy process and machine learning, calculating a comprehensive capability value and defining a learning hierarchy; personalized teaching plans are formulated for students at different levels, such as high-level matching of high-difficulty practice tasks and subject research, low-level strengthening of basic knowledge and the like. And new data is collected every week to dynamically adjust the level and the teaching plan. According to the system and method, multiple factors are comprehensively considered, accurate teaching is achieved through AI, and the teaching effect and student ability are improved.

The invention discloses a smart home control method and system based on graph retrieval enhanced generation and multi-agent gaming, and the method comprises the steps: constructing a basic knowledge graph based on a current smart home environment, carrying out the semantic enrichment of service entities in the basic knowledge graph, generating an enhanced knowledge graph, and storing the enhanced knowledge graph in a vector database; constructing an example library containing a plurality of formalized observation-logic hypothesis pairs; acquiring a situation snapshot of the user, and outputting a structured scene analysis report based on the situation snapshot and the vectorization database through a front-end LLM; collaborative review is carried out by combining a factor-tracing reasoning agent, a user preference agent and a conflict detection agent with a scene analysis report and an example library, and a final decision is output by a core decision LLM and mapped into an equipment control instruction to call corresponding equipment for execution. According to the method, the fuzzy instruction of the user is combined with the knowledge graph, so that the intention recognition accuracy is improved; the multi-agent parallel auditing mechanism improves the robustness and safety of decision making.

The invention discloses a knowledge graph construction method and device, a storage medium and electronic device.The method comprises the steps that a comprehensive data set is constructed, accurate semantic relation representation is determined by recognizing entities in the comprehensive data set and relations between the entities, similar entities in the comprehensive data set are fused on the basis of the semantic relation representation, and the knowledge graph is obtained. In combination with heterogeneous data fusion, a basic knowledge framework is constructed, new knowledge is generated by utilizing an inference engine based on airspace monitoring requirements and the basic knowledge framework, and an airspace target knowledge graph is constructed in combination with an anomaly detection mechanism. The accuracy, reliability and safety of airspace target monitoring are improved, and intelligent development of airspace monitoring is promoted.

The present invention relates to the field of wood processing technology, and more specifically to a continuous fixed-width cutting system and method for wooden doors and door frames, comprising: an instruction input module, the instruction input module including a plate width input unit and a plate quantity input unit; a fixed-width module, the fixed-width module including a laser sensor, a plate drive component, and a controller, the laser sensor emitting a laser light path, and generating an action signal according to a state change of the laser light path at a first position. The present invention aims to simplify the cutting process. After a worker fills in a plate and inputs the size and quantity of a target plate, the system can automatically measure the width of the plate and complete the cutting of the target plate in order from wide to narrow. Workers do not need to participate in plate measurement and how to distribute the remaining material during the cutting process. This is very beneficial for workers with no basic knowledge, and enterprises can also reduce training costs and improve production efficiency.

The embodiment of the invention relates to the technical field of knowledge maps, and particularly discloses a knowledge map construction method and system for enterprise dynamic risks. According to the embodiment of the invention, risk original information is obtained; performing entity, attribute, relation and time information extraction on the risk original information; performing unified processing of entity linking, attribute merging and relation conflict resolution on the multiple pieces of structured information; constructing a basic knowledge graph; and based on the basic knowledge graph, constructing a dynamic risk model, performing future relationship prediction and risk trend prediction, and generating and displaying dynamic prediction information. According to the method, time span credibility evaluation and timeliness conflict interval positioning are carried out on multi-source attributes, the problems of attribute description conflicts and timeliness dislocation in multi-source data are effectively solved, meanwhile, permeation expression of risk signals on the attribute level is enhanced, and a consistent data basis is provided for accurate enterprise risk portraits.

The invention relates to the technical field of artificial intelligence, and provides a robot control method, device and equipment based on security enhancement and a medium, which can be applied to financial and medical health care service scenes, and can construct a security knowledge system of a target environment to provide comprehensive and structured security basic knowledge. Task disassembling is carried out according to the control instruction, then a security constraint label is added to each sub-task in a sub-task sequence according to a security knowledge system to obtain a sub-task label sequence, and thus security elements are fused into the sub-tasks; according to the method, the subtask labeling sequence is input into the security risk assessment model, and the security optimization is performed on the subtask sequence according to the risk prediction data, so that the subtask sequence can be adjusted in a targeted manner after the security risk in the subtask sequence is accurately identified, the security risk is effectively reduced, and the security and feasibility of the subtask sequence are ensured; and the robot is controlled to execute the safety subtask sequence, so that the safety and rationality of the robot control process are improved.

The invention belongs to the technical field of power failure repair, and provides an intelligent generation method and system for a power failure repair scheme, and the method comprises the steps: constructing a multi-modal instruction template, obtaining the basic knowledge of the power industry, constructing a data set, training a general large language model through the data set, and employing a hierarchical learning rate strategy to achieve the intelligent generation of the power failure repair scheme. Obtaining a large language model after fine tuning of domain knowledge; obtaining a power failure first-aid repair case, constructing the power failure first-aid repair case as a sample according to a pre-constructed multi-modal instruction template, and optimizing the parameters of the large language model finely adjusted by the domain knowledge by using the sample by taking semantic loss, physical constraint loss and safety loss as a weighted mixed loss function; obtaining a large language model after multi-modal task fine tuning; and processing the target data by using the large language model subjected to multi-modal task fine tuning to obtain a final power failure repair scheme. According to the invention, the accuracy and intelligence of power fault first-aid repair scheme generation are improved.

The invention discloses a network security dynamic early warning method and system based on a knowledge graph, and relates to the technical field of network security early warning, and the method comprises the steps: collecting the original data Raw of a network security event, analyzing core network entities and the interaction relationship thereof, constructing a structured basic knowledge graph KG, constructing a behavior feature algorithm based on the core network entities and the interaction relationship thereof, and carrying out the dynamic early warning of the network security. The method comprises the steps of generating a behavior feature set CE, generating a potential attack path set CP based on dynamic trigger points of the behavior feature set CE, screening a high threat path pmax in combination with a candidate path propagation score pps, calculating a threat index ATI to generate an early warning report AS, and performing linkage response action and closed-loop optimization. According to the method, the scattered events are associated as the attack chain through the knowledge graph, the risk is dynamically quantified, the threshold value is adaptively adjusted, the problems that early warning is lagged, the false alarm rate is high and multi-stage attacks cannot be associated in a traditional method are solved, and the early recognition and blocking capacity of complex threats is remarkably improved.

The invention relates to the technical field of artificial intelligence, in particular to a child education quality analysis method and system based on artificial intelligence, and aims to evaluate education quality based on basic knowledge point learning influence analysis results of children and learning conditions of corresponding links of child courses. The score condition of the basic knowledge points of the corresponding students and the influence degree of the basic knowledge points are comprehensively considered, the learning influence condition of the students is comprehensively evaluated through a formula, and the limitation that only a single factor is concerned is avoided. In this way, the learning condition of students on each basic knowledge point and the influence of the knowledge points on the overall learning of the students can be more accurately known, in education quality evaluation, the teaching score condition of child courses and the basic knowledge point influence analysis result are comprehensively considered, and through a teaching quality analysis formula, the teaching quality of the students can be evaluated. The influence coefficient of previous knowledge points on courses is fully considered, so that the education quality evaluation is more comprehensive and reasonable.

The embodiment of the invention discloses a method for training a large language model for health notification. The scheme can comprise the following steps: acquiring initial training data; the initial training data comprises sample data and label data for the sample data; the sample data comprises a user input sample and a first health notification text; according to the incidence relation data, knowledge extension information for the user input sample is generated; the association relationship data is used for reflecting an association relationship among a plurality of pieces of data extracted from a preset text and basic knowledge of a field to which the preset text belongs; the preset text at least comprises a first health notification text; generating training sample data based on the initial training data and the knowledge extension information; and performing supervised fine tuning training on the pre-trained large model by using the training sample data to obtain a large language model for health notification.

The invention belongs to the technical field of virtual training analysis, and particularly relates to an online virtual psychological training scoring system and a scoring method thereof. Comprising a training simulation module, a simulation evaluation module, a database module, a wide area network module, a management end and a student end. The training simulation module comprises a simulation server and a simulation output unit; the simulation evaluation module comprises an identity management unit, an index management unit and an evaluation unit; the database module is used for providing data support and processing service for each resource of the system and generated data; the wide area network module is used for establishing contact between equipment in the system and the management end and the student end; the management end is used for establishing an interface and a control mechanism related to system configuration management and system monitoring; and the student end is used for establishing a simulation training and student interaction operation mechanism. The virtual psychological training system is used for online virtual psychological training, meets the requirements of vocational skill training of related posts and the like, and enables learners to be familiar with and master basic knowledge, basic processes and practical operation skills of psychological training.

The invention provides a knowledge graph construction method and system for intelligently fusing multi-modal data, and the system employs a layered architecture, and comprises a data input layer, a mode special extractor, a multi-modal aligner, a graph construction / mining device, and a multi-modal retrieval service layer. The modular design enables the system to have good expandability and maintainability, and each module can be independently developed and optimized. The characteristics of different modal data are fully utilized, and the efficiency and accuracy of feature extraction are improved. Through the accurate alignment processing, the accuracy of entities and relationships in the knowledge graph can be effectively improved, and the alignment error is reduced. The deep association relationship among the entities in the basic knowledge graph is mined through the configured deep association mining engine, so that potential knowledge hidden in data can be found, and the content of the knowledge graph is enriched. A user can obtain knowledge from multiple angles, different application requirements are met, and the utilization efficiency of the knowledge is improved.

The application discloses a knowledge graph construction method and device of a promotion path, wherein the method comprises the following steps: step S1, combing core concepts related to the promotion path and semantic relations thereof, constructing a basic knowledge framework, and creating an ontology model based on the basic knowledge framework; step S2, setting mapping rules between ontology data and a graph database, and mapping the ontology model to the graph database; step S3, collecting multi-source information, performing knowledge extraction on the multi-source information to obtain knowledge triples and constructing entities, and constructing a knowledge graph by comprehensively combining the ontology model and the entities; and step S4, performing retrieval and correlation analysis based on the knowledge graph, forming promotion path instances, dynamically updating the promotion path instances to the knowledge graph, and obtaining a promotion path knowledge graph. The promotion path knowledge graph is obtained based on dynamic updating of the knowledge graph.

The invention relates to a digital delivery-based building operation and maintenance corpus construction method, which comprises the following four core processes: step 1, constructing a footstone corpus containing structured multi-source information based on building full-life-cycle digital delivery data; 2, generating professional question and answer pairs covering multiple categories in combination with operation and maintenance scenes and expert experience; 3, marking a decision-making thinking chain containing a judgment basis, an analysis process and a processing suggestion for the complex scene; and step 4, establishing a multi-dimensional evaluation system covering basic knowledge, problem solving, professional decision making and innovation ability. By integrating full-life-cycle digital delivery data, hierarchical construction of corpora from foundation to complexity is achieved, the speciality and effectiveness of the corpora are guaranteed through quantitative quality evaluation and a dynamic optimization mechanism, the problems that existing corpora are single in data and lack of deep decision knowledge are solved, and the method has the advantages of being high in practicability and easy to popularize. High-quality data support is provided for special large model training in the field of building operation and maintenance, and intelligent upgrading of operation and maintenance is promoted.

The application discloses a kind of based on multi-task depth knowledge tracking method and device, wherein the method comprises: obtaining the question representation, the knowledge point representation and the answer correctness result of all time before current time;Input the question representation, the knowledge point representation and the answer correctness result to the knowledge tracking model after training for processing;And, in response to the processing of the knowledge tracking model, obtain the knowledge point answer correctness result of next time;Wherein, the knowledge tracking model is based on the specified knowledge tracking network, including the first auxiliary task component for predicting the knowledge point corresponding to the question of current time t and the basic knowledge tracking task component for predicting the knowledge point answer correctness result of next time t+1. The present application scheme simultaneously predicts the knowledge point input by student at current time and predicts the historical overall answer accuracy of student at each time step on the basis of the basic task of predicting the correctness of question to be answered by student, and improves the evaluation effect of doing question.

The invention discloses a Unity-based cable accessory installation training system and a construction method thereof. The system comprises a basic knowledge learning module, a professional knowledge learning module, a training examination module, an examination evaluation module and the like. The basic knowledge learning module provides content such as identification graphs related to cable accessory installation, electrical instruments, tool use and safety specifications and the like, and teaching is assisted in a visual mode of images, texts, voice and structures. The professional knowledge learning module is used for displaying key installation processes and process standards in the forms of three-dimensional animation, video explanation, structure explosion diagram and the like; the training examination module is provided with basic examination and practical operation examination, and supports question bank import, interactive answering and action monitoring; and the assessment and evaluation module performs statistical analysis on assessment data and generates visual assessment reports such as a radar map and the like. According to the invention, the learning efficiency of trainees can be improved, the training cost is reduced, the training safety and flexibility are enhanced, and standardization, intelligence and high efficiency of cable accessory installation skill training and assessment are realized.

The invention discloses a marketing product knowledge graph construction method and device, and belongs to the technical field of data processing, and the method comprises the steps: constructing a weighted directed graph comprising user nodes, dish nodes, dish category nodes and consumption scene nodes as a basic knowledge graph; collecting time, weather and geographic position signals in real time, calculating a scene influence value through a quantization algorithm, and dynamically updating a relation weight by adopting a multiplication correction model; performing correlation intensity, diversity and novelty optimal path search in parallel on the dynamic map, and outputting an equilibrium path set based on Pareto optimal selection; generating a multi-modal marketing content package in combination with the user request, the real-time scene and the marketing target; the efficiency is evaluated through A / B test, and the click rate and the order-placing conversion rate are used as reward signals to be fed back to the weight correction process. Through the design of dynamic perception, multi-target collaboration and intelligent generation, the accuracy, diversity and real-time performance of the recommendation system are remarkably improved.

The application discloses a work order processing method, device and equipment and a readable storage medium. After obtaining a to-be-processed work order, first, first prompt information for processing the work order and indicating summarizing the content of the work order is determined, then, based on the first prompt information, the summary content of the work order is obtained; then, based on the summary content of the work order, whether there is a similar question to the summary content of the work order in a basic knowledge base is searched, and a first search result is obtained; finally, according to the first search result, the work order is processed, and a reply corresponding to the work order is obtained. Based on the scheme, automatic work order processing can be realized, and more efficient and high-quality government affairs question answering can be realized.

The invention provides an intelligent data resource table entering system based on a knowledge graph, and belongs to the field of knowledge graphs. Comprising a data acquisition unit, a basic atlas construction unit, a relation correction optimization unit and an evaluation table entry unit. Wherein the data acquisition unit is used for acquiring a target data resource to be entered into a table; the basic graph construction unit is used for constructing a basic knowledge graph; the relation correction optimization unit is used for adjusting the basic knowledge graph to obtain the knowledge graph; and the evaluation table entry unit is used for analyzing and obtaining the resource fitness of the target data resource according to the scale of the knowledge graph and the data volume of the multiple groups of data, and identifying the knowledge graph and storing the knowledge graph in a table. According to the method and the device, the technical problem of low data resource management efficiency caused by the fact that the data value and the association relationship cannot be accurately evaluated during data resource storage in the prior art is solved, and the technical effect of realizing accurate quantitative evaluation and efficient table entry management of the data resource value by constructing the knowledge graph and calculating the resource fitness is achieved.

The system according to this embodiment aims to enable beginners to efficiently learn the basic knowledge of app development and actually develop apps. [Solution] The system according to the embodiment comprises a provisioning unit, a designing unit, and a testing unit. The provisioning unit provides educational materials for beginners to learn the basic knowledge of app development. When a user inputs an app idea, the designing unit generates an app design based on that idea using a generation AI, and then performs coding. The testing unit automatically verifies the app's operation using the generation AI, detects bugs, and corrects them.