Yung Taek Kim

Also published as: Yung-Taek Kim


2000

pdf bib
Machine translation systems: E-K, K-E, J-K, K-J
Yu Seop Kim | Sung Dong Kim | Seong Bae Park | Jong Woo Lee | Jeong Ho Chang | Kyu Baek Hwang | Min O Jang | Yung Taek Kim
Proceedings of the Fourth Conference of the Association for Machine Translation in the Americas: User Studies

We present four kinds of machine translation system in this description: E-K (English to Korean), K-E (Korean to English), J-K (Japanese to Korean), K-J (Korean to Japanese). Among these, E-K and K-J translation systems are published commercially, and the other systems have finished their development. This paper describes the structure and function of each system with figures and translation results.

pdf bib
Word Sense Disambiguation by Learning from Unlabeled Data
Seong-Bae Park | Byoung-Tak Zhang | Yung Taek Kim
Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics

pdf bib
Reducing Parsing Complexity by Intra-Sentence Segmentation based on Maximum Entropy Model
Sung Dong Kim | Byoung-Tak Zhang | Yung Taek Kim
2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora

1999

pdf bib
Compound noun decomposition using a Markov model
Jongwoo Lee | Byoung-Tak Zhang | Yung Taek Kim
Proceedings of Machine Translation Summit VII

A statistical method for compound noun decomposition is presented. Previous studies on this problem showed some statistical information are helpful. But applying statistical information was not so systemic that performance depends heavily on the algorithm and some algorithms usually have many separated steps. In our work statistical information is collected from manually decomposed compound noun corpus to build a Markov model for composition. Two Markov chains representing statistical information are assumed independent: one for the sequence of participants' lengths and another for the sequence of participants ' features. Besides Markov assumptions, least participants preference assumption also is used. These two assumptions enable the decomposition algorithm to be a kind of conditional dynamic programming so that efficient and systemic computation can be performed. When applied to test data of size 5027, we obtained a precision of 98.4%.

1994

pdf bib
Syllable-Based Model for the Korean Morphology
Seung-Shik Kang | Yung Taek Kim
COLING 1994 Volume 1: The 15th International Conference on Computational Linguistics

1993

pdf bib
An Idiom-based Approach to Machine Translation
Hagyu Lee | Yung Taek Kim
Proceedings of the Fifth Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages

pdf bib
Towards a Machine Translation System with Self-Critiquing Capability
Kwangseob Shim | Yung Taek Kim
Proceedings of the Fifth Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages

1990

pdf bib
Morphological Analysis and Synthesis by Automated Discovery and Acquisition of Linguistic Rules
Byoung-Tak Zhang | Yung-Taek Kim
COLING 1990 Volume 2: Papers presented to the 13th International Conference on Computational Linguistics

1989

pdf bib
Analysis Techniques for Korean Sentences Based on Lexical Functional Grammar
Deok Ho Yoon | Yung Taek Kim
Proceedings of the First International Workshop on Parsing Technologies

The Unification-based Grammars seem to be adequate for the analysis of agglutinative languages such as Korean, etc. In this paper, the merits of Lexical Functional Grammar is analyzed and the structure of Korean Syntactic Analyzer is described. Verbal complex category is used for the analysis of several linguistic phenomena and a new attribute of UNKNOWN is defined for the analysis of grammatical relations.