[논문]Ranking Translation Word Selection Using a Bilingual Dictionary and WordNet

Kim, Kweon-Yang; Park, Se-Young

doi:10.5391/jkiis.2006.16.1.124

Ranking Translation Word Selection Using a Bilingual Dictionary and WordNet 원문보기

퍼지 및 지능시스템학회 논문지 = Journal of fuzzy logic and intelligent systems, v.16 no.1, 2006년, pp.124 - 129

Kim, Kweon-Yang (School of Computer Engineering, Kyungik University) , Park, Se-Young (Dept. of Computer Engineering, Kyungpook National University)

Abstract ▼ AI-Helper

This parer presents a method of ranking translation word selection for Korean verbs based on lexical knowledge contained in a bilingual Korean-English dictionary and WordNet that are easily obtainable knowledge resources. We focus on deciding which translation of the target word is the most appropriate using the measure of semantic relatedness through the 45 extended relations between possible translations of target word and some indicative clue words that play a role of predicate-arguments in source language text. In order to reduce the weight of application of possibly unwanted senses, we rank the possible word senses for each translation word by measuring semantic similarity between the translation word and its near synonyms. We report an average accuracy of $51\%$ with ten Korean ambiguous verbs. The evaluation suggests that our approach outperforms the default baseline performance and previous works.

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In their experiments, they used the seven possible relations such as synset, hypernym, hyponym, holonym, meronym, troponym, and attribute of each word sense in WordNet. In effect, the glosses of surrounding words in the context are expanded to include glosses of theses related words to which they are semantically related through the extended relations in WordNet.
In this paper, we present a method of ranking translation words that attempts to select the most appropriate translation word for Korean verbs using the measure of semantic relatedness that the WordNet similarity pack- age[10] provides. Knowledge sources are extracted from a bilingual Korean-English dictionary and WordNet.
for Korean transitive verbs. Therefore we decided to adopt the three major predicate-argument r이成ions such as Noun-'ulV'rur (object) + Verb, Noun-'ae' (locative) + Verb, and Noun-'roV'uro' (instrument) + Verb rather than immediate surrounding words to improve the performance of translation word selection.

참고문헌 (10)

Banerjee, S. and Pedersen, T., 'Extended. Gloss Overlaps as a Measure of Semantic Relatedness,' Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, pp. 805-810, 2003
Brown, P., Cocke, J, Pietra, V., Peitra, S., Jelinek, F., Lafferty, J., Mercer, R. and Roosin, P., 'A Statistical Approach to Machine Translation, Computational Linguistics,' Vol. 16, No.2, pp. 79-85, 1990
Dagan, I. And Itai, A, ''Word Sense Disambiguation Using a Second Language Monolingual Corpus,' Computational Linguistics, Vol. 20, No. 4, pp. 563-596, 1994

상세보기
Fellbaum, c., WordNet: An Electronic Lexical Database, MIT Press, 1998
Inkpen, D. and Hirst, G., 'Automatic' Sense Disambiguation of the Near-Synonyms in a Dictionary Entry,' Proceedings, Fourth Conference on Intelligent Text Processing and Computational Linguistics, pp. 258-267, 2003

상세보기
Jiang, J. and Conrath, D., 'Semantic Similarity based on Corpus Statistics and Lexicon Taxqnomy,' Proceedings on International Conference on Research in Computational Linguistics, pp. 19-33, 1997
Koehn, P. and Knight K., 'Knowledge Sources for Word-Level Translation Models,' Empirical Methods in Natural Language Processing Conference, pp. 27-35, 2001
Lesk, M., 'Automatic Sense Disambiguation Using Machine Readable Dictionaries: how to tell a pine code from an ice cream cone,' Proceedings. of the Fifth Annual International Conference on Systems Documentations, pp. 24-26, 1986
Li, H. and Li, C., 'Word Translation Disambiguation Using Bilingual Boostrapping,' Computational Linguistics, Vol. 30, No.1, pp. 1-22, 2004

상세보기
Patwardhan, S. and Perdersen, T., The cpan wordnet::similarity package, http://search.cpan.org /~sid/WordNet-Similarity-0.06/, 2005

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