Seonho Kim


2005

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Two-Phase Biomedical Named Entity Recognition Using A Hybrid Method
Seonho Kim | Juntae Yoon | Kyung-Mi Park | Hae-Chang Rim
Second International Joint Conference on Natural Language Processing: Full Papers

2001

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Improving Lexical Mapping Model of English-Korean Bitext Using Structural Features
Seonho Kim | Juntae Yoon | Mansuk Song
Proceedings of the 2001 Conference on Empirical Methods in Natural Language Processing

2000

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Structural Feature Selection For English-Korean Statistical Machine Translation
Seonho Kim | Juntae Yoon | Mansuk Song
COLING 2000 Volume 1: The 18th International Conference on Computational Linguistics

1999

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Retrieving Collocations From Korean Text
Seonho Kim | Zooil Yang | Mansuk Song | Jung-Ho Ahn
1999 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora

1997

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Ambiguity Resolution Using Lexical Association
Juntae Yoon | Seonho Kim | Mansuk Song
ROCLING 1997 Poster Papers

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New Parsing Method using Global Association Table
Juntae Yoon | Seonho Kim | Mansuk Song
Proceedings of the Fifth International Workshop on Parsing Technologies

This paper presents a new parsing method using statistical information extracted from corpus, especially for Korean. The structural ambiguities are occurred in deciding the dependency relation between words in Korean. While figuring out the correct dependency, the lexical associations play an important role in resolving the ambiguities. Our parser uses statistical cooccurrence data to compute the lexical associations. In addition, it can be shown that sentences are parsed deterministically by the global management of the association. In this paper, the global association table (GAT) is defined and the association between words is recorded in the GAT. The system is the hybrid semi-deterministic parser and is controlled not by the condition-action rule. but by the association value between phrases. Whenever the expectation of the parser fails, it chooses the alternatives using a chart to remove the backtracking.