19 results about "Concept map" patented technology

A method, apparatus, and storage medium for constructing and managing a knowledge graph. The construction method is applied to an oilfield water gathering, transportation, and injection system. The knowledge graph includes a concept graph. The method includes: acquiring text data related to energy consumption control in the oilfield water gathering, transportation, and injection system, wherein the text data records anomaly analysis information and resolution process information; treating parameter anomalies, anomaly causes, handling measures, and at least one piece of information used to characterize the event localization process as entities in the concept graph; performing entity recognition on the text data to obtain naming information for each type of entity in the text data; obtaining entity relationships between different types of entities in the text data based on the entity naming information; and generating the concept graph based on the entity relationships in the text data.

The application provides a kind of personalized learning path recommendation method based on reinforcement learning, it is related to educational data mining technical field.The method first constructs learner simulator according to the learning record of scholar, the simulator can judge the learning level of learner;Then the knowledge relationship graph between the knowledge points contained in the exercise is automatically constructed by the concept map automatic construction model based on text classification and association rule mining;Based on the knowledge relationship graph and the cognitive diagnosis model, an exercise navigation module is designed to select potential candidate exercises;After the reinforcement learning agent selects the action in the action space, the state transition is determined in the state space, the model parameters are updated according to the loss function and optimization strategy, and the reinforcement learning model is optimized;Finally, the designed reinforcement learning model is used to recommend exercises for learners, and the reinforcement learning model parameters are updated according to the learning situation of learners.The method can recommend efficient and reasonable learning path for learners.

The application discloses a kind of aspect-level sentiment analysis method based on multilevel knowledge enhancement, belong to sentiment analysis field. Including the following steps: S1: text word vector is obtained using GloVe word embedding tool, the syntax dependency tree of sentence is constructed using Stanza, and the dependency graph is constructed accordingly;S2: the context representation of sentence is extracted by inputting word vector into BiLSTM, and the dependency graph is updated using sentiment dictionary and sensitive relationship set, to realize the sentiment and syntax enhancement of sentence;S3: the enhanced dependency graph is input into GCN to model node features, to obtain specific aspect representation;S4: aspect word is enhanced using concept atlas to obtain aspect word representation, which is fused with specific aspect representation to obtain aspect representation;S5: aspect representation and context representation are coordinated and optimized using interactive attention, to obtain the final representation of sentence, so as to determine aspect sentiment tendency.The application can effectively improve the accuracy of specific aspect sentiment classification, and help merchants accurately locate problems in products or services.

The application provides a model digital generation type design method and device based on a continuous implicit function, and relates to the technical field of artificial intelligence, which comprises the following steps: performing copyright and trademark similarity detection processing on design requirement information to obtain target design requirement information, and sending the target design requirement information to a conditional diffusion model to generate a two-dimensional concept map of a to-be-rendered jewelry; performing implicit three-dimensional reconstruction processing on the two-dimensional concept map to obtain a jewelry three-dimensional geometric model, and performing automatic matching processing on the jewelry three-dimensional geometric model to obtain a jewelry target three-dimensional geometric model containing physical material parameters; performing physical rendering processing and image enhancement processing on the jewelry target three-dimensional geometric model to obtain a multi-angle high-definition rendering map of the jewelry, and sending the jewelry target three-dimensional geometric model and the multi-angle high-definition rendering map as target output to a user end. The application can significantly improve the accuracy and model construction efficiency of jewelry three-dimensional model construction.

The application discloses a large-scale Chinese painting generation interaction method based on multi-emotion recognition, which comprises the following steps: obtaining input data of a user and extracting tone prompt words in the input data; inputting the tone prompt words into a pre-trained emotion analysis model to generate corresponding emotion labels; inputting the emotion labels into a diffusion model to generate a concept picture, and performing semantic retrieval on a pre-built Chinese painting element knowledge base to screen out a historical painter and corresponding life events that are most similar to the emotion labels; using natural language generation technology to perform text fusion on the emotion labels, image information in the concept picture and the screened life events to output a final personalized interpretation text; and finally, visualizing and outputting the interaction result. The application further provides a large-scale Chinese painting generation interaction device. The method provided by the application can intelligently understand user emotions and automatically generate Chinese painting works with a high degree of artistic conception matching.

The invention discloses a method and a computer program product for carrying out conceptual graph visual interaction on an online education platform. The method comprises the following steps: S1, obtaining a conceptual graph drawn by a student user; s2, establishing an online virtual classroom for a teacher user and all student users of the class; s3, executing the following steps on each conceptual graph: sharing and displaying the conceptual graph; discussing and scoring the conceptual graph by each student user through voice interaction, and carrying out associated storage on voice information input by each student user, a user account and the conceptual graph; according to the voice information of the student user, the score of the student user on the conceptual graph is determined; determining a comprehensive score according to scores of all student users on the conceptual graph; and S4, selecting the conceptual graph with the optimal comprehensive score from the conceptual graphs. According to the invention, teaching interaction between teachers and students is greatly facilitated, the students can systematically sort knowledge through teaching interaction of the conceptual graph, and the students can be promoted to consolidate the knowledge, train the thinking ability and improve the innovation ability.

The invention provides an intelligent analysis system for students to self-adjust learning strategies. The system comprises a data acquisition and preprocessing layer, a text processing and enhancement layer, a core analysis layer and an application display layer. The data acquisition and preprocessing layer comprises an audio acquisition module and a voice transcription and structuring module, the text processing and enhancement layer comprises a text cleaning module and a semantic normalization module, and the core analysis layer comprises a concept map analysis module and a learning strategy analysis module. And the application display layer comprises a visual rendering module and an instrument panel integration module. According to the invention, total, objective and real-time collection of classroom discussion data is realized, and subjectivity and hysteresis of manual recording are eliminated; through deep semantic analysis, the knowledge structure of discussion content is disclosed, and core technical support is provided for empirical research of cultivating self-adjustment learning ability of students based on an intelligent learning analysis tool.

Provided is a schematic interactions visualization (SIV) system for innovative education, which relates to the technical field of innovative education. The key points includes six key technologies: a spatial acoustic medicine technology, a course exploration technology of cross-disciplinary theme extraction for discipline bottlenecks, a SIV cross-disciplinary model design based on projects, a SIV course design technology for interactions strategy of disciplinary schemata, a SIV strategy of technology design for critical interactions events, and an evaluation technology design for individual works of thematic-concept-map.

The invention discloses an adversarial text graph LoRA sample generation method and system for safety assessment, and belongs to the field of artificial intelligence safety. Defining two adversarial scene types including a concept hijacking scene and an adversarial task injection scene, and constructing an adversarial data set; the method comprises the following steps: constructing a target concept image and a tampering text for a concept hijacking scene, and recording a trigger word related to a target concept; aiming at an adversarial task injection scene, an adversarial trigger word and a target concept need to be predefined; obtaining a benign LoRA and a corresponding benign data set, and training a LoRA plug-in by a multi-objective optimization training method according to the benign data set and the adversarial data set; and traversing different benign LoRA and antagonistic scenes to obtain a plurality of trained LoRA plug-ins for evaluating the AI security system. The LoRA sample generated by the method has high verisimilitude and concealment, novel security risks can be disclosed, and defense technology iteration is promoted.

The invention relates to the technical field of hierarchical industry classification, in particular to a hierarchical industry classification method and system based on AI semantic analysis. Comprising the steps of constructing an industrial knowledge base and an intelligent agent; collecting multi-modal data of a to-be-evaluated enterprise, and generating a business association packet of the to-be-evaluated enterprise by the intelligent agent according to the multi-modal data; generating an assessment path set of the to-be-assessed enterprise according to the industrial knowledge base and the business association packet; and constructing a hierarchical industry classification model according to the evaluation path set. The business basic portrait is established by collecting public data of an enterprise, the training mapping set of the to-be-evaluated enterprise is dynamically adjusted, and the semantic analysis model matched with the to-be-evaluated enterprise is quickly established, so that semantic interference of irrelevant industries is effectively shielded, the accuracy of business concept extraction is improved, and the classification accuracy and the adaptability to emerging business forms are improved; and a double-path verification model is constructed based on semantic vector similarity retrieval and business concept map reasoning, so that the business analysis efficiency is improved, and the industrial requirements of multi-standard hierarchical classification are met.

The application discloses a kind of based on visual concept map representation Man-model interaction explanation guide method, electronic equipment and storage medium, the method includes: with model as foundation extraction important image block as category concept, constructs structure concept map, to this as tool representation arbitrary image, again build feature flow transparent inference network simulation existing classification network, observe the contribution of each part of concept map, to realize the explainability of decision;On the other hand, people independently each component as a concept, attribute arrangement is carried out to component, and structure component diagram is constructed in combination with component relationship.Based on this, people can update structure concept map with the structure component diagram of category, retrain inference network, and then guide knowledge to original network by knowledge distillation.Based on this two-way interaction method, the application can provide reasoning logic that people can understand by model, realize the explainability of neural network;Meanwhile, allow people to provide feedback to network using prior knowledge, to improve the performance of network.

To evaluate a process in which a learner reconfigures a concept map.SOLUTION: The system 100 for supporting learning in which a learner reconstructs a concept map on a UI screen includes a problem presentation part 42 for presenting a plurality of concept nodes and a plurality of movable parts of inter-concept links obtained by decomposing a correct concept map 32 on an UI screen 50, a part operation determination part 62 for determining that an arbitrary node and an arbitrary link are connected or separated on the UI screen 50, a history recording part 64 for recording the formation history of propositions represented by these links and nodes in a log 33 when arbitrary two nodes are connected to both ends of an arbitrary link, a history extraction part 44 for extracting the formation history of propositions matching propositions included in a correct concept map 32 from the log 33, and a history recording part 46 for evaluating temporal continuity of proposition formation for each sub-map of the correct concept map 32 from the extracted formation history of propositions. And an evaluation part 46 for evaluating the concept map reconfiguration process by the learner on the basis of the evaluation result.SELECTED DRAWING: Figure 2

The invention relates to the technical field of data processing, and discloses a code page generation method and system based on AI and a historical page, and the method comprises the steps: obtaining historical page configuration data stored in a code platform, analyzing the historical page configuration data based on an AI algorithm, mining a business concept entity and a business operator, and generating the business concept entity and the business operator; meanwhile, on the basis of data processing, the logic dependency relationship among the elements is recognized, a domain service concept map is generated, through the generated domain service concept map, conversion from isolated component features to a semantic service knowledge system is achieved, complex service association among the components is accurately captured, and through a declarative data flow diagram, the content of the components in the domain service knowledge system is improved. According to the method, data format compatibility and transmission efficiency are ensured, rapid delivery of a platform native application package is realized through an executable application mirror image and a hot deployment mechanism, and it is ensured that the generated code user interface has a complete service function and stable operation performance.

This invention discloses a concept graph-based method for enhancing astronomical computational reasoning instructions, comprising the following steps: obtaining seed problems labeled with subdomains and topics as basic input; extracting knowledge points from the seed problems using a large language model to establish a knowledge framework covering subdomains, topics, and knowledge points; and transforming problem instances into conceptual representations; constructing a concept graph based on the knowledge framework; executing a dynamic random walk algorithm on the concept graph to output a complete concept combination; and using the complete concept combination to guide the large language model in generating astronomical computational problems and corresponding reasoning processes through example matching, data deduplication, and thought chain distillation. This invention, by constructing a concept graph and employing a random walk strategy, improves the diversity and logical rigor of the generated data, providing a new path for optimizing astronomical computational reasoning instructions.

The invention relates to the technical field of artificial intelligence, can be applied to the medical field and the financial insurance field, and discloses a question and answer data generation method and device based on a conceptual graph, equipment and a storage medium. The method comprises the steps of extracting question and answer pair data from seed data of a preset field to construct a seed data set; extracting a theme set and a knowledge point set from the seed data set, and constructing a mapping relationship between themes in the theme set and knowledge points in the knowledge point set; constructing a conceptual graph based on the topic set, the knowledge point set and the mapping relation, and calculating the weight of edges between nodes in the conceptual graph to obtain a weighted conceptual graph; performing semantic random walk and combined sampling on the weighted conceptual graph to generate a combined path set; and generating a question and answer data sample set based on the combined path set through the large language model, and verifying the question and answer data sample set to generate a target question and answer data sample set. The question and answer data generation accuracy is improved.

Techniques for fine-tuning a pre-trained vector embedding model for recommending standard codes for mapping with proprietary codes are disclosed. Proprietary codes, as referred to herein, include reference codes particular to organizations or vendors. Standard codes, as referred to herein, are industry or standardized codes. The system access a candidate set of standard codes that have been mapped to one or more proprietary codes. The system determines a number of times a standard code is mapped to a proprietary code. Standard codes that have been mapped to proprietary codes a number of times that meet a threshold are selected to be included in a training set for fine-tuning the pre-trained vector embedding model. Standard codes with a number of mappings that does not meet the threshold are not included in the training set. The system may also use vector embedding models for generating aggregated datasets for datasets of the training set.

The invention discloses a collaborative design method and device for a compressor unit oil supply system based on a COMOS platform, and the method comprises the steps: selecting a target configuration template from a preset configuration template library of the COMOS platform based on a design demand file; creating a project directory in the COMOS platform based on the target configuration template; based on the predefined type of the modular configuration component, building a modular configuration component instance under the item directory, and configuring component parameters based on the parameter attributes; according to actual module group division of the compressor unit oil supply system, the modular configuration assembly examples are classified into corresponding function modules; calling a pre-associated engineering object and a standard symbol in the target configuration template, creating a modular engineering basic object, and generating a Pamp according to the modular engineering basic object; according to the method, a COMOS platform, an ID drawing, a modular conceptual graph and engineering nodes are used for completing the Pamp of the oil supply system of the compressor unit; and automatically drawing an ID general drawing, and synchronously generating an instrument control data table.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for using a concept graph to select relevant tables relevant for querying a database. In particular, in some embodiments, the disclosed systems generate concept tags for tables in a database schema based on content of the tables corresponding to concepts in a list of concepts. Additionally, the disclosed systems generate a concept graph comprising hyper edges linking the tables to the concepts according to the concept tags. The disclosed systems determine, from the tables in the database schema, a set of tables relevant to a natural language query comprising an indicated concept by extracting the set of tables from one or more hyper edges corresponding to the indicated concept from the concept graph. The disclosed systems also generate, utilizing a large language model, a response for the natural language query from the set of relevant tables.