Seonho Kim
2005
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
Seonho Kim | Juntae Yoon | Kyung-Mi Park | Hae-Chang Rim
Second International Joint Conference on Natural Language Processing: Full Papers
2001
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
Seonho Kim | Juntae Yoon | Mansuk Song
Proceedings of the 2001 Conference on Empirical Methods in Natural Language Processing
2000
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
Seonho Kim | Juntae Yoon | Mansuk Song
COLING 2000 Volume 1: The 18th International Conference on Computational Linguistics
1999
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
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
New Parsing Method using Global Association Table
Juntae Yoon | Seonho Kim | Mansuk Song
Proceedings of the Fifth International Workshop on Parsing Technologies
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.