41 results about "Knowledge modelling" patented technology

The invention belongs to the technical field of knowledge management and knowledge pushing oriented to manufacturing enterprises, particularly relates to a novel and efficient knowledge management and knowledge pushing method based on a knowledge graph and discloses a knowledge pushing method based on a manufacturing design knowledge graph structure (Man-tree). By means of the method, the comprehensiveness and accuracy of enterprise knowledge pushing can be effectively improved. The knowledge pushing method comprises the step that a knowledge modeling module, a knowledge extracting and subject discovering module, a knowledge graph Man-tree establishing module, a user knowledge possess degree calculation module and a knowledge pushing module are established by introducing an LDA method. By quantitatively evaluating the degree of the knowledge processed by a user, the knowledge graph is expanded, and semantic association between knowledge and the user is established. According to the specific technology, formation of a database, extraction of knowledge, discovery of knowledge association, knowledge storage design, and a quantitative calculating method for the degree of the knowledge processed by a user are included. The novel method for knowledge pushing in the manufacturing design field is given on the basis that the manufacturing design graph is proposed.

The invention relates to an electric power communication network knowledge graph construction method based on a BERT model, and the method comprises the following steps: S1, original document library construction: selecting data of different sources and structures as a basis, and constructing the original document library; S2, label migration: labeling the original knowledge data of the power communication network, and carrying out label migration on the basis of labeling information; S3, semantic feature extraction: performing training based on a BERT model to realize semantic feature extraction of the structured document data of the power communication network; and S4, knowledge graph construction: performing named entity identification on the extracted semantic features based on a BiLSTM-CRF model, extracting knowledge concepts and interrelations, and forming the knowledge graph in cooperation with knowledge modeling. The method effectively solves the typical problems of many professional terms, few training corpora and the like, improves the accuracy of key steps such as named entity recognition and the like, and finally improves the performance of the knowledge graph.

A collaborative recommendation model construction method based on knowledge graph preference propagation comprises the following steps: (1) performing knowledge modeling by using an ontology modeling tool, extracting entities and relationships to obtain a triple, and constructing a domain knowledge graph; (2) obtaining multi-layer preferences of the user through the preference propagation model, and calculating vector representation of the user preferences according to the multi-layer preferences of the user; (3) learning the vector representation of the article based on the user-article interaction matrix, and performing dot product operation on the preference vector representation of the user and the implicit vector representation of the article to calculate the click probability of the user on the article; and (4) recalling articles interested by the user according to the click probability, comparing a recall result with a user interaction list, and performing descending sorting after excluding the articles operated by the user to obtain a recommendation list. According to the recommendation model provided by the invention, the path structure information of the knowledge graph can be fully utilized, and the interpretability and diversity of recommendation results are improved.

The invention discloses an equipment resource configuration optimization method based on knowledge graph driving. The method comprises the steps that a knowledge graph of manufacturing resources is organized and generated, and machining process knowledge modeling and workshop machining equipment modeling are involved; the formed knowledge graph is subjected to a distributed representation learningand resource prediction matching method, and the relation between the knowledge graph and mining manufacturing resource implicit knowledge is further represented; when a processing order is issued, acandidate equipment set is constructed in combination with a fuzzy hierarchy method based on knowledge graph driving, and further the candidate equipment set is evaluated and screened through a community load model to complete reconstruction of the manufacturing unit; and finally, configuration optimization of an order task is completed by utilizing an optimization algorithm of the resource configuration mathematical model, an available processing equipment set link is formed, and a production process is guided. According to the method provided by the invention, the data processing capabilityis enhanced to a great extent, the equipment utilization rate and the equipment processing flexibility are improved, and meanwhile, the optimal configuration cost of manufacturing resources requiredby a processing task is also reduced through integrated knowledge reuse.

The embodiment of the invention provides an ancient poem proposition method. The method comprises the following steps: extracting at least one keyword of each poem in a poem training set based on a knowledge graph, determining the keyword as a semantic feature of each poem, and modeling the semantic feature of each poem by using a neural network to obtain a poem model of which the input is the semantic feature of the poem and the output is other semantic features with similar semantics; carrying out knowledge modeling on the poem training set by utilizing the knowledge graph to obtain a structured model of poem information in the poem training set; and associating the poem model and the structured model based on the semantic features of each poem, inputting a preset question type into theassociated poem model and structured model, and outputting a question corresponding to the preset question type. The embodiment of the invention further provides an ancient poem proposition system. According to the embodiment of the invention, modeling is carried out by using the semantic features of the poems, the relation words of the poems can be distinguished, rich poem information can be obtained by structuring the information of the poems, and questions with higher quality can be generated.

The invention discloses a disaster chain-based multi-disaster coupling and secondary derivative evolution prediction system. The system comprises a disaster chain correlation knowledge modeling module, a multi-disaster emergency dynamic comprehensive management module and a multi-disaster coupling prediction module, the disaster chain correlation knowledge modeling module is used for constructinga disaster chain for natural disasters by using a disaster source to form a semantic network graph, and representing disaster chain knowledge by using a Bayesian network method in combination with actual background demand analysis of a cause and effect type disaster chain; the multi-disaster emergency dynamic comprehensive management module is used for realizing dynamic management of real-time processing, analysis and decision of natural disaster information; and the multi-disaster coupling prediction module divides a disaster chain-based prediction process into single-disaster prediction andmulti-disaster coupling prediction according to two factors of catastrophe and a disaster-affected body. According to the invention, through the multi-disaster coupling evolution model, occurred disasters can be analyzed in an omnibearing and multi-angle manner, and various emergency treatments after the disasters occur can be carried out.

The invention provides a knowledge graph construction method and device. The method comprises the following steps: acquiring original data and a large-scale knowledge graph; performing knowledge modeling on the original data to obtain a knowledge modeling result; generating concept layer data based on the knowledge modeling result and the large-scale knowledge graph; performing knowledge acquisition on the original data, including entity extraction, entity classification and first entity attribute extraction, to obtain entities, entity categories and entity attributes; inputting the entity as a keyword into the large-scale knowledge graph, and obtaining entity related information of the entity; fusing the entity, the entity category, the entity attribute and the entity related information to obtain complete entity layer data; and constructing a new knowledge graph based on the concept layer data and the entity layer data. According to the method, construction of the knowledge graph is achieved, and meanwhile updating of the knowledge graph in the using process can be achieved through the steps.

A computer-integratable global knowledge modeling system comprising electronic means for expressing a plurality of entity representations interconnected by relations is described, wherein the entity representations, comprising modeling base elements and rules, are organized according to a fine-grained hierarchical or fractal structure, the relations between entity representations being highly detailed; a plurality of variants, representing each a particular point of view, are associated to at least a part of an entity representation in order to customize the corresponding entity representation; and the knowledge modeling system is usable in an adaptive computer-executable artifact.

The invention discloses a clinical guideline knowledge modeling method and system. The method comprises the following steps: acquiring a clinical guideline data set; performing text analysis on the clinical guideline data set, and generating document layer information; based on the document layer information, determining a hierarchical structure corresponding to each version of clinical guidelines and module content corresponding to each hierarchy, and generating module layer information; subjecting module content in the module layer information to knowledge-based processing, and obtaining knowledge layer information which represents knowledge graph information of the clinical guidelines; and constructing an association relationship among the document layer information, the module layer information and the knowledge layer information, generating an association relationship library, and visually displaying the association relationship library to obtain a cross-layer multi-dimensional association model. According to the technical scheme, the clinical guidelines of different versions are standardized and integrated, layer-by-layer display of the association relationship and content of the guideline information is facilitated, application requirements for clinical guideline knowledge is met, and the practicability of clinical guideline knowledge modeling is improved.

The invention discloses a power communication network intelligent auxiliary operation and maintenance method and system based on a knowledge graph, and the method comprises the following steps: constructing a power communication network intelligent auxiliary operation and maintenance architecture based on the knowledge graph, wherein the architecture comprises a data collection layer, a knowledgeobtaining layer, a knowledge fusion layer, a knowledge storage layer, and a knowledge service layer, and the core module comprises a knowledge modeling module, an intelligent interaction module and aknowledge operation and maintenance module. Based on various data and operation management modes, multivariate data is fused, communication network intelligent auxiliary operation and maintenance of the knowledge graph are achieved, barriers among multi-system, multi-dimensional and multi-structure data are broken through, the intelligent interaction capacity is improved, and knowledge support foron-site operation and maintenance is achieved.

The invention discloses an intelligent fishery question-answering robot construction method based on a knowledge graph, and the method comprises the steps: carrying out the building of a knowledge modeling structure through referring to the semantic division of other fields at present; by researching semi-structured and non-structured data in the fishery field, restoring a service mode in the fishery production process, stripping semantic types and semantic relations of fishery knowledge, and extracting an object body; extracting ontology attributes and examples of the corresponding object ontology from the crawled structured data; and performing knowledge fusion on the crawled structured data and data from a third-party knowledge base, and finally obtaining a complete construction methodof the intelligent fishery question-answering robot based on the knowledge graph by embedding the intelligent fishery question-answering robot using the AIML technology into a Web page. According to the invention, the construction integrity rate of a knowledge concept system in the field is improved, a more convenient way is provided for farmers to obtain required information, and the production efficiency can be improved.

The invention relates to a regulation and control knowledge modeling method based on a BiLSTM technology, and the method comprises the steps: constructing a power domain ontology based on the BiLSTM technology, extracting conceptual entities in the ontology, combining the conceptual entities to obtain basic terms, and manually determining important terms in the basic terms; dividing the importantterms into three categories: department units, behavior categories and information data, and defining inheritance structures among the categories by adopting a top-down method; defining attributes andconstraints of the class, thereby creating an instance of the class; and outputting the instantiated ontology according to the input text and the created instance of the class. A professional knowledge framework can be provided for regulation and control personnel, and sharing of regulation and control professional knowledge in the electric power field is achieved.

The invention relates to an intelligent fault processing system and a method, and a storage medium, and the system comprises a fault knowledge modeling module, and a minimum-function assembly appearing in a server system, and the fault knowledge modeling module and the minimum-function assembly serve as vertexes and are inputted into a graph database; wherein possible faults of each component serve as 'attributes' to be affiliated to the component, and the'attributes' and the component are recorded into a graph database together; for any two associated components, respectively designing a corresponding relationship, and inputting the corresponding relationship into a graph database as an edge; and a fault grading and processing mode confirmation module which is used for defining the stateof each component, establishing a relationship between the states and the corresponding processing modes, and recording the relationship as an edge into a graph database. A central control unit is connected with the monitoring system and the graph database in a butt joint mode, and the monitoring system feeds back monitored assembly changes to the central control unit in real time; and the centralcontrol unit searches a corresponding processing strategy from the graph database according to the component fault and adopts a corresponding fault processing action.

The invention provides an encyclopedia-based cross-language knowledge graph construction method and device, and the method comprises the steps: obtaining original encyclopedia data of a target field,and enabling the original encyclopedia data to comprise at least two languages and at least two sources of original data of the target field; preprocessing the original encyclopedia data to obtain preprocessed target data; based on the preprocessed target data, executing knowledge modeling operation, and obtaining concept data, hyponymy relations between different concepts and concept attribute data; based on the preprocessed target data, executing knowledge acquisition operation to obtain instance data, a relationship between an instance and a concept and instance attribute data; and executing knowledge fusion operation to generate a knowledge graph of the target domain. According to the method, the construction of the encyclopedia-based cross-language domain knowledge graph is realized,data sources are diversified, and the construction efficiency of the knowledge graph can be effectively improved.

The invention discloses a Pu'er tea field knowledge graph construction method and device, and relates to the technical field of Pu'er tea, and the method comprises the steps: building a Pu'er tea field first-layer knowledge ontology classification model; establishing a Pu'er tea field second-layer knowledge ontology classification model; and establishing a Pu'er tea field knowledge entity model associated with the first-layer knowledge ontology classification model and the second-layer knowledge ontology classification model for constructing the Pu'er tea field knowledge graph. According to the method, a construction mode of expanding from the center to the periphery is adopted, two-level knowledge ontology classification is performed on the Pu'er tea field knowledge, an entity model is extracted in combination with a knowledge ontology classification model feature word library, and the entity model is associated with a knowledge ontology classification model to form the Pu'er tea field knowledge graph. By adopting the method, the complex relationship between the entity models can be managed in a classified manner through the knowledge ontology, the dependence on professionals in the incremental knowledge extraction process is reduced, and the knowledge modeling accuracy is improved.

The invention provides a question generation method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a to-be-processed knowledge sub-graph from a knowledge graph, the knowledge graph being obtained by carrying out graph structuring on a knowledge text, and part of nodes in the knowledge sub-graph carrying answer node marks; the knowledge sub-graphs are input into a question generation model, a question text output by the question generation model is obtained, the question generation model is obtained through training based on a sample question text and a corresponding sample knowledge sub-graph, part of nodes in the sample knowledge sub-graph carry sample answer node labels, and a knowledge graph of non-strict ontology constraint is constructed; the domain correlation between the knowledge text and the knowledge graph is ensured, the knowledge modeling fineness is improved, the influence of noise in the knowledge text is reduced, the defect that in a traditional scheme, a question and answer pair generation method is not suitable for a long knowledge text is overcome, the utilization rate of structural information of the long knowledge text is improved, and the user experience is improved. The problem text is generated.

The invention discloses a knowledge modeling method and system for intelligent calculation and adjustment of power flow of a power grid. The method comprises the following steps: dividing knowledge involved in intelligent calculation and adjustment of the power flow of the power grid into power grid data knowledge, power grid state knowledge and adjustment rule knowledge; representing the power grid data knowledge, the power grid state knowledge and the adjustment rule knowledge in a triple form, and constructing a knowledge base; and according to the currently known facts, the power grid data knowledge, the power grid state knowledge and the adjustment rule knowledge in the knowledge base are utilized, performing reasoning according to a reasoning method and a control strategy, updating and prefecting the knowledge base, and ensuring the correctness and integrity of the knowledge.