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Research in Thesaurus-based Ontology Building Method

Author: LiMengSha
Tutor: JiangTongQiang
School: Beijing Technology and Business University
Course: Management Science and Engineering
Keywords: Ontology Learning Body automatically build Thesauri conversion Natural Language Processing
CLC: TP391.1
Type: Master's thesis
Year: 2010
Downloads: 72
Quote: 0
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Abstract


Ontology building can be divided into two types: one is based on the experts in the field of hand-built; built based on machine learning, automatic / semi-automatic. Former labor work as the main semantic content, build body depends on the personal knowledge of the builders, so this way the knowledge bottleneck problem just played a relief role. The latter is the automatic acquisition of knowledge through machine learning information from the mass, is an important way for a fundamental solution to the ontology building in the knowledge bottleneck problem. About body automatically build more and more aspects of the research, however ontology construction in the field dependence, low degree of automation, the learning effect is not ideal, and so the problem has not been a good solution. Chinese ontology construction, at home and abroad are very few Chinese body automatically build. Therefore, on the basis of in-depth study on the current ontology construction and ontology learning method, proposed new ideas to automatically build a domain ontology, and focuses on the following aspects: (1) a field-based thesauri ontology learning system model. Technology, the model thesauri body conversion technology and ontology learning in relationships to get use of the inherent advantages of thesauri, to make up for ineffective due to the relationship between the concept and the classification ontology learning process and on the basis of the relationship between learning the plain text data source, access to non-classified relations between concepts, domain ontology building richer semantic information. (2) design and thesauri-based domain ontology learning system. Thesauri-based domain ontology learning system is divided into learning modules the thesauri conversion module as well as non-taxonomic relations. In the thesauri conversion module, this article summarizes the of a field thesauri body conversion rules, to the field of initial body conversion and use as the basis for the realization of a thesaurus. Non-taxonomic relationship learning module, extended association rule mining method as the theoretical basis for Chinese natural language processing technology of Chinese Corpus relations obtain, and studying the relationship between the results added to the initial ontology. (3) use the system to build domain ontology and evaluated. The evaluation of the body has not yet formed standards, this article only choice reusability, scalability degree of correlation reference several indicators of the body automatically build evaluate the results. The paper designs and implements thesauri-based domain ontology learning system for the Chinese areas of the body automatically build valuable reference, and specific applications of semantic knowledge based on Chinese body has a positive meaning.

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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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