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공공누리This item is licensed Korea Open Government License

Title
A term normalization method for efficient knowledge acquisition through text processing
Author(s)
황명권정도헌김진형송사광정한민
Publication Year
2012-06-03
Abstract
The importance of research on knowledge management is growing due to recent issues on Big Data. One of the most fundamental steps in knowledge management is the extraction of terminologies. Terms are often expressed in various forms and the variations often play a negative role, becoming an obstacle which causes knowledge systems to extract unnecessary ones. To solve the problem, we propose a method of term normalization which finds a normalized form (original and standard form defined in dictionaries) of variant terms. The method employs two characteristics of terms: appearance similarity measuring how similar terms are, context similarity measuring how many clue words they share. Through experiment, we show its positive influence of both similarities in term normalization.
Keyword
Term normalization; Knowledge acquisition; Text mining; Appearance similarity; Context similarity
Journal Title
MultimediaToolsandApplications
Citation Volume
65
ISSN
1380-7501
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Appears in Collections:
7. KISTI 연구성과 > 학술지 발표논문
URI
https://repository.kisti.re.kr/handle/10580/14085
http://www.ndsl.kr/ndsl/search/detail/article/articleSearchResultDetail.do?cn=NART65799354
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