지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.8 No.3
- 발행연도
- 2014.9
- 수록면
- 137 - 148 (12page)
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초록· 키워드
오류제보하기
Named entity classification of Wikipedia articles is a fundamental research area that can be used to automatically build large-scale corpora of named entity recognition or to support other entity processing, such as entity linking, as auxiliary tasks. This paper describes a method of classifying named entities in Chinese Wikipedia with fine-grained types. We considered multi-faceted information in Chinese Wikipedia to construct four feature sets, designed different feature selection methods for each feature, and fused different features with a vector space using different strategies. Experimental results show that the explored feature sets and their combination can effectively improve the performance of named entity classification.
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. RELATED WORK
Ⅲ. NAMED ENTITY TYPE
Ⅳ. FEATURES EXTRACTION
Ⅴ. EXPERIMENTS
Ⅵ. CONCLUSIONS
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2015-560-002699354