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Book body matching method based on machine learning

A technology of machine learning and matching method, applied in the direction of instruments, special data processing applications, network data retrieval, etc., can solve problems such as failure to meet practical requirements, inability to analyze and excavate the characteristics of the book field, and unsatisfactory matching effect.

Active Publication Date: 2015-04-01
SOUTHEAST UNIV
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AI Technical Summary

Problems solved by technology

However, there is no ontology matching system for the book field at present. Only a domain-independent ontology matching system is used to match the ontology of the book field, which cannot analyze and dig out the inherent characteristics of the book field ontology, so the matching effect is not satisfactory. , does not meet the practical requirements

Method used

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  • Book body matching method based on machine learning
  • Book body matching method based on machine learning
  • Book body matching method based on machine learning

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Embodiment Construction

[0049] The implementation process of the present invention will be described in detail below in conjunction with the embodiments and the accompanying drawings.

[0050] The ontology matching method based on machine learning of the present invention comprises the following 3 steps:

[0051] 1) For the given two book ontologies to be matched, generate the instance pair set IP to be matched and the concept pair set CP to be matched:

[0052] Ontology is a specification proposed by the World Wide Web Consortium (W3C) for describing various resource information on the World Wide Web. The ontologies described in the present invention are all ontologies in the field of books, which are composed of book concepts, instances, attributes, and relationships. An instance refers to a specific object, a concept refers to an object type or a collection of instances, an attribute refers to the possible characteristics of an object or concept, and a relationship refers to the way objects, conce...

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Abstract

The invention discloses a book body matching method based on machine learning, and mainly aims to solve the problem of difficulty in realizing body matching in the field of book processing. The method comprises the following steps: generating all instance pairs and concept pairs to be matched for two given book bodies, and mining equivalence relations between instances from all the instance pairs to be matched by using a heuristic instance matching rule and a decision model based on supervised learning in order to obtain an instance matching result; mining hyponymy relations and equivalence relations between concepts for all the concepts to be matched by using a label propagation algorithm based on semi-supervised learning in order to obtain a concept matching result; finally, combining the instance matching result and the concept matching result for serving as a book body matching result.

Description

technical field [0001] The invention belongs to the field of ontology matching, and relates to a book ontology matching method based on machine learning. Background technique [0002] In recent years, with the continuous development of the Semantic Web, more and more knowledge is published in the Web in the form of ontology. As a new and representative form of knowledge representation, ontology plays an important role in the development and deployment of the Semantic World Wide Web. More and more organizations and individuals build ontology-based applications in different fields, including e-commerce , life sciences, social media, geographic information, etc. With the continuous increase of the number of ontologies in the Internet, there must be multiple ontologies originating from related or same application domains. Since different ontologies from related or same domains have different construction methods, they must have great information complementarity, which implies ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/951
Inventor 吴天星漆桂林罗斌陆彬
Owner SOUTHEAST UNIV
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