Juntae Yoon


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

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Identifying Temporal Expression and its Syntactic Role Using FST and Lexical Data from Corpus
Juntae Yoon | Yoonkwan Kim | Mansuk Song
COLING 2000 Volume 2: The 18th International Conference on Computational Linguistics

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Towards Translingual Information Access using Portable Information Extraction
Michael White | Claire Cardie | Chung-hye Han | Nari Kim | Benoit Lavoie | Martha Palmer | Owen Rainbow | Juntae Yoon
ANLP-NAACL 2000 Workshop: Embedded Machine Translation Systems

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Customizing the XTAG system for efficient grammar development for Korean
Juntae Yoon | Chung-hye Han | Nari Kim | Meesook Kim
Proceedings of the Fifth International Workshop on Tree Adjoining Grammar and Related Frameworks (TAG+5)

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Compound Noun Segmentation Based on Lexical Data Extracted from Corpus
Juntae Yoon
Sixth Applied Natural Language Processing Conference

1999

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Corpus-Based Approach for Nominal Compound Analysis for Korean Based on Linguistic and Statistical Information
Juntae Yoon | Key-Sun Choi | Mansuk Song
1999 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora

1997

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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.

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