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153 results about "Knowledge representation and reasoning" patented technology

Knowledge representation and reasoning (KR², KR&R) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can utilize to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning, such as the application of rules or the relations of sets and subsets.

Dynamic learning and knowledge representation for data mining

An integrated human and computer interactive data mining method receives an input database. A learning, modeling, and analysis method uses the database to create an initial knowledge model. A query of the initial knowledge model is performed using a query request. The initial knowledge model is processed to create a knowledge presentation output for visualization. It further comprises a feedback and update request step that updates the initial knowledge model.
A multiple level integrated human and computer interactive data mining method facilitates overview interactive data mining and dynamic learning and knowledge representation by using the initial knowledge model and the database to create and update a presentable knowledge model. It facilitates zoom and filter interactive data mining and dynamic learning and knowledge representation by using the presentable knowledge model and the database to create and update the presentable knowledge model. It further facilitates details-on-demand interactive data mining and dynamic learning and knowledge representation by using the presentable knowledge model and the database to create and update the presentable knowledge model.
The integrated human and computer interactive data mining method allows rule viewing by a parallel coordinate visualization technique that maps a multiple dimensional space onto two display dimensions with data items presented as polygonal lines.
Owner:LEICA MICROSYSTEMS CMS GMBH

Building method and system used for knowledge obtaining model in knowledge graph

The invention provides a building method used for a knowledge obtaining model in a knowledge graph. The method comprises the steps of constructing a first training set consisting of multiple text sentences as input data and a relationship between any two entities in each sentence in the knowledge graph, as a classification result, and training a first neural network; constructing a second trainingset consisting of triples in multiple knowledge graphs, and training a second neural network; by taking input data vectors obtained in the second neural network as attention features of the first neural network, building a relationship extraction model; by taking input data vectors obtained in the first neural network as attention features of the second neural network, building a knowledge representation model; and fusing the relationship extraction model and the knowledge representation model to obtain the knowledge obtaining model in the knowledge graph. According to the method provided bythe invention, the two task models of knowledge representation and relationship extraction are integrated at the same time, and the features of the knowledge graph and free texts can be comprehensively extracted, so that the model stability and accuracy are improved.
Owner:TSINGHUA UNIV

Keyword based evaluation expert intelligent search and recommendation method

The invention discloses a keyword based evaluation expert intelligent search and recommendation method. The keyword based evaluation expert intelligent search and recommendation method specifically comprises step 1, segmenting an expert information main text into substring sequences, performing ICTCLAS word segmentation of Chinese academy of sciences and performing stop word filtering on the result of the word segmentation to obtain the word collection; step 2, extracting feature words of the expert information according to fields; step 3, building an expert knowledge representation model based on the fields and the weight of the feature words and establishing an expert information index database; step 4, performing automatic prompting according to a search term thesaurus when a user inputs keywords and meanwhile performing real-time update on the search term thesaurus through a search term counter; step 5, calculating the search relevance between the keywords and the expert information based on the semantic information and the like; step 6, listing relevant experts from high to low according to the matching degree. According to the keyword based evaluation expert intelligent search and recommendation method, the intelligent full-text search and recommendation of the expert information can be achieved through the keyword input and accordingly the experts which are matched with a pended science and technology project can be searched out accurately.
Owner:HANGZHOU DIANZI UNIV

Intelligent review expert recommending method for science and technology projects

The invention provides an intelligent review expert recommending method for science and technology projects. The method includes the following steps that (1) the science and technology projects to be reviewed and expert information main texts are segmented into substring sequences, ICTCLAS segmentation of Chinese academy of sciences is carried out on the substring sequences, and stop word filtering is carried out on a segmentation result to obtain a term set; (2) a term network of project information is built, feature words are extracted on the basis of statistical characteristics and aggregation characteristics, and if expert information is relatively concise, the term set obtained in the step (1) directly serves as the feature words; (3) a knowledge representation model is built on the basis of fields and weights of the feature words, and a relative information index is built; (4) experts are recommended in groups to carry out feature merging operations between the fields and between the projects on the knowledge representation model; (5) similarity of the experts and the science and technology projects or groups to be viewed is calculated on the basis of semantics, threshold truncation is set, and a final recommended expert list is generated. By means of the method, the problems that recommending workload is large and review decisions lack scientificity are greatly alleviated.
Owner:HANGZHOU DIANZI UNIV

Power distribution network fault diagnosis system and method based on multi-source information

The invention discloses a power distribution network fault diagnosis system and method based on multi-source information. The system comprises a data collection layer, a knowledge representation layer and a fault diagnosis layer, wherein the data collection layer collects fault warning information in each power distribution substation and provides the collected information for the knowledge representation layer in time sequence; the knowledge representation layer describes and buffers data of all kinds of data sources of the information and provides all kinds of heterogeneous data for the fault diagnosis layer in a unified data view mode; the fault diagnosis layer makes different diagnosis methods according to the different data sources, a fault result is comprehensively judged finally, and the diagnosis result is used for analysis after an accident. The utilization rate of the fault information is improved, the reliability of the fault diagnosis is ensured, the fault reason, the fault influence degree and the like are analyzed preliminarily after a fault happens, the analysis result can assist operating personnel in building a timely and effective power distribution network fault repairing strategy, and the power supply reliability of a power distribution network is improved.
Owner:STATE GRID CORP OF CHINA +1

Information resource query recommendation method and system based on knowledge graph

The invention provides an information resource query recommendation method and system based on a knowledge graph, and the method comprises the steps: carrying out the preprocessing of the knowledge graph, enabling the knowledge graph to be mapped to a low-dimensional dense vector space through employing a representation learning method, and obtaining the vector representation of an entity; calculating the interest degree of the user in the information resource according to the historical behavior of the user, and constructing a user interest model by combining the vectorized representation ofthe information resource and the interest degree of the user in the information resource; achieving accurate recommendation of the information resources is achieved by calculating the similarity between the resources and the similarity between the users and the resources. According to the invention, the knowledge graph representation learning is combined with the user interest model to provide personalized service for the user; according to the method, the internal relation of knowledge and the interest of the user are considered, and the information resources related to the query content andconforming to the interest of the user are recommended to the user according to the queried resource name input by the user, so that the personalized query recommendation is more professional and targeted.
Owner:HOHAI UNIV

Onsite information preprocessing method of remote cooperative diagnosis

An onsite information preprocessing method of remote cooperative diagnosis includes an information collection step, a health state prediction step, a deep information processing step and a remote information transmission step. The information collection step collects working state information, control information, fault diagnosis information, working record information and working environment information. The health state prediction step predicates health state of equipment in one further period according to collection information and correspondingly conducting adjustment on an important monitoring point and monitoring frequency of the state monitoring in advance. The deep information processing step excavates fault sign information of relative time periods of the important monitoring point and conducting effective information extraction on common health state information according to certain standard. The remote information transmission step uploads preprocessing results. The onsite information preprocessing method compresses and extracts onsite original data of the equipment, reasonably expresses health state information of the equipment and converts the health state information into the knowledge expression mode required by an expert system or other decision making systems according to actual health state of the equipment.
Owner:XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY

Knowledge graph-based mechanical fault diagnosis knowledge base construction method

The invention discloses a knowledge graph-based mechanical fault diagnosis knowledge base construction method, and belongs to the field of mechanical fault diagnosis. A mechanical fault diagnosis knowledge base reflects fault generation essences and domain expert experiences; and through a knowledge processing module, the fault generation essences and the domain expert experiences are stored in the knowledge base, thereby providing support for mechanical fault diagnosis. A conventional knowledge graph is represented in a network form; nodes represent entities; connection lines represent relationships; and for the representation form, a special graph algorithm needs to be designed for storing and utilizing a database, so that the disadvantage of time and labor waste exists. According to a representation learning technology represented by deep learning, a triple object is mapped to a vector space and represented as a dense low-dimensional vector, and efficient calculation and reasoning are realized through vector conversion. The knowledge graph-based mechanical fault diagnosis knowledge base construction method is established; mechanical fault diagnosis knowledge is represented as atriple, and the tripe is represented as the vector by utilizing a TransD model, so that the problems of inaccurate case representation, difficult maintenance and modification, low reasoning and calculation efficiency and the like of a conventional knowledge base can be optimized; and the method has important significance for the field of fault diagnosis.
Owner:BEIJING UNIV OF CHEM TECH
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