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Ontology inclusion axiom learning method based on linear programming

A technology of linear programming and learning methods, applied in the field of representation learning and ontology construction of knowledge graphs

Pending Publication Date: 2020-03-17
TIANJIN UNIV
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[0004] The purpose of the present invention is to provide a linear programming-based ontology inclusion axiom learning method, which not only constructs a representation learning model that combines types and relations, but also uses the linear representation learning model to capture predicate features, and obtain the ontology inclusion relationship by summarizing and reducing the inclusion relationship into a linear program, and can still efficiently learn the corresponding ontology when the knowledge graph is incomplete

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  • Ontology inclusion axiom learning method based on linear programming
  • Ontology inclusion axiom learning method based on linear programming
  • Ontology inclusion axiom learning method based on linear programming

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[0025] If certain words are used to refer to specific components in the specification and claims, those skilled in the art should understand that the manufacturer may use different terms to refer to the same component. The specification and claims do not use the difference in name as a way to distinguish components, but use the difference in function of components as a criterion for distinguishing. As mentioned throughout the specification and claims, "comprising" is an open term, so it should be interpreted as "including but not limited to". "Approximately" means that within an acceptable error range, those skilled in the art can solve technical problems within a certain error range and basically achieve technical effects.

[0026] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "upper", "lower", "front", "rear", "left", "right", horizontal" etc. are based on the drawings The orientatio...

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Abstract

The invention belongs to the technical field of knowledge graph representation learning and ontology construction, concretely relates to an ontology inclusion axiom learning method based on linear programming. The method comprises the following steps: constructing a representation learning model SetE, inputting entity data, type data and relationship data of a knowledge graph Abox into the representation learning model SetE, calculating inclusion relationships among the type data, and extracting the inclusion relationships to form axioms. According to the method, predicate features can be captured by using a linear representation learning model, the inclusion relation is concluded and reduced into linear programming to obtain the ontology inclusion relation, and the corresponding ontologycan still be efficiently learned under the condition that the knowledge graph is incomplete.

Description

technical field [0001] The invention belongs to the technical field of knowledge graph representation learning and ontology construction, and in particular relates to a linear programming-based ontology inclusion axiom learning method. Background technique [0002] Ontology is the description of concepts and attributes in the knowledge graph, and it is also a combination of types and relationships. Ontology inclusion axiom refers to the axiom that describes the inclusion relationship in the knowledge graph data. Although OntoEdit, Protege, and Ontolingua in the prior art can construct ontology from several data information stored in the knowledge map Abox, the inventors found that it is difficult to express the logical relationship contained in the ontology in the prior art, and the construction process of the ontology Difficulties remain. Moreover, the automatic construction of ontology has always been a difficult point in knowledge representation and machine learning. ...

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Application Information

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IPC IPC(8): G06F16/28G06F16/36
CPCG06F16/367G06F16/288
Inventor 赵乐园张小旺冯志勇
Owner TIANJIN UNIV
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