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서술어 Bigram을 이용한 단어 유사도 측정

Word Similarity Based on Predicate-Argument Bigrams in Morphologically Analyzed Corpora

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참고문헌

키워드

주제분류언어학

초록

In this paper, I suggested a statistical method to measure word similarity using predicate-argument relations in bigrams from a morphologically analyzed corpus. A word network can contribute to semantic processing in natural language processing. In recent works, word networks have been constructed by the human intuition, but it spends a lot of time and lacks consistency and relevant evaluation method. Statistical methods can relate syntactic information to the human intuition. To retrieve the syntactic information from corpus, I referred to bigram-context, containing <Noun, Predicate> pairs. While English needs accurate syntactic analyses, bigram-context in Korean corpus represents enough syntactic features, especially the predicate-argument relations, because the grammatical morphemes of Koran language show the syntactic information. I used the Dekang Lin(1998) and the Weighted Jaccard(Gasperin et al., 2001) Measure for word similarity. The synonym list extracted from corpus covered 40% (recall) of synonyms in three Korean dictionaries.

Abstract

In this paper, I suggested a statistical method to measure word similarity using predicate-argument relations in bigrams from a morphologically analyzed corpus. A word network can contribute to semantic processing in natural language processing. In recent works, word networks have been constructed by the human intuition, but it spends a lot of time and lacks consistency and relevant evaluation method. Statistical methods can relate syntactic information to the human intuition. To retrieve the syntactic information from corpus, I referred to bigram-context, containing <Noun, Predicate> pairs. While English needs accurate syntactic analyses, bigram-context in Korean corpus represents enough syntactic features, especially the predicate-argument relations, because the grammatical morphemes of Koran language show the syntactic information. I used the Dekang Lin(1998) and the Weighted Jaccard(Gasperin et al., 2001) Measure for word similarity. The synonym list extracted from corpus covered 40% (recall) of synonyms in three Korean dictionaries.

참고문헌 (22)

  1. 국립국어원, "한국어 어휘의망 구축의 현황과 과제", 한국어 어휘의미망 구축과 사전 편찬 학술회의 (2007)
  2. 신효필, "미크로코스모스 온톨로지로의 한국어 기본 동사의 사상", 언어학, (49), pp.305~324 (2007), 한국언어학회
  3. 윤애선, "한국어 어휘의미망 구축의 현황과 과제", 한국어 어휘의미망 구축과 사전편찬 학술회의 (2007), 국립국어원
  4. 이성헌, "전자사전 구축을 위한 언어기술의 한 방법", 언어학, (30), pp.185~206 (2001), 한국언어학회
  5. 최호섭,옥철영, "한국어 의미망 구축과 활용- 명사를 중심으로 -", 한국어학, 17, pp.6~330 (2002), 한국어학회
  6. Collins, A., "A spreading activation theory of semantic processing", Psychological Review, 82, pp.407~428 (1975)
  7. Dekang Lin, "Information Theoretic definition of similarity", Proc. 15th International. Conf. on Machine Learning (1998)
  8. Fellbaum,C., "WordNet:An Electronic Lexical Database" (1998), MIT Press
  9. Gasperin A., "Syntactic-Based Methods for Measuring Word Similarity", Proceedings of TSD 2001,?4th?International Conference on Text, Speech and Dialogue, pp.116~125 (2001), Czech Republic
  10. Grefenstette,G., "Evaluation techniques for automatic semantic extraction: Comparing syntactic and window-based approaches", In Proceedings of the Workshop on Acquisition of Lexical Knowledge from Text (1992)
  11. Lee,L., "Similarity-based approaches to natural language processing", 박사, pp.1997
  12. Miller,G., "WordNet: An on-line lexical database", International Journal of Lexicography, 3(4) (1990)
  13. Quillian,M.R., "Semantic Memory, Semantic Information Processing" (1968), MIT Press
  14. Rada,R., "Ranking documents with a thesaurus", JASIS, 40(5), pp.304~310 (1989)
  15. Rada,R., "Development and application of a metric on semantic nets", IEEE Transaction on Systems Man and Cybernetics, 19(1), pp.17~30 (1989)
  16. Resnik,P., "WordNet and class-based probabilities" (1998), An Electronic Lexical Database, MIT Press
  17. Resnik,P., "Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language", Journal of Artificial Intelligence Research, 11, pp.95~130 (1999)
  18. Richardson,R., "Using WordNet as a knowledge base for measuring semantic similarity between words, Working paper CA-1294, Dublin City University, School of Computer Applications, Dublin, Ireland, 젨젨쟣tp:", pub, pp.w-papers, 1994[DOI]
  19. Stijn van Dongen, "Graph Clustering by Flow Simulation", 박사, pp.2000
  20. Sussna,M., "Word sense disambiguation for free-text indexing using a massive semantic network", In Proceedings of the Second International Conference on Information and Knowledge Management (1993)
  21. Yarowsky,D., "Word sense disambiguation using statistical models of Roget's categories trained on large corpora", Proceedings of the 14rh International Conference on Computational linguistics, COLING '92, pp.454~460 (1992)
  22. Young C.Park, "Automatic Thesaurus Construction Using Bayesian Networks", Information Processing & Management, 32(5) (1996)

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