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Reseraching of Transfer Learning Methods Based on Optimized Ontology
Author: LiYunHong
Tutor: TianHong
School: Dalian Jiaotong University
Course: Applied Computer Technology
Keywords: Body Concept lattice Optimization Concept similarity Transfer learning
CLC: TP391.1
Type: Master's thesis
Year: 2010
Downloads: 79
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Abstract
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In recent years, more and more about the main body in the computer science . The so - called body , the most famous and widely referenced definition : \Popular talk , the body is used to describe a field of even broader range of concepts and relations between the concepts , making these concepts and relations have common recognized , clear , only the definition within the shared , so between man and machine , and the machine can communicate . At present , the body has been widely used in Semantic Web, intelligent information retrieval , information integration, digital libraries, information exchange between people and organizations in areas such as . The core concepts of the body is knowledge sharing, by reducing the ambiguity of the concepts and terminology , the ontology of an organization or working group to provide a unified framework or normative model , so that personnel from different backgrounds , took a different view and purpose intercultural understanding and exchange possible and maintain the semantic consistency . This paper mainly focus on the concept of similarity and optimize the body 's transfer learning method to expand . The papers detailed analysis of the classic ontology generation method . Text generation algorithm based on the combination of formal concept analysis and statistical learning ontology concept lattice is constructed to ontology mapping process . At the same time , using an optimization algorithm to optimize the main body . In addition, in the ontology mapping process , some of the inadequacies of the existing ontology mapping of conceptual similarity , given an improved method of conceptual similarity . Concept similarity calculation method based on this improved method gives an optimization study the migration of the main body . Finally, given the transfer learning ontology model .
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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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