Resolving translation ambiguity and target polysemy in cross-language information retrieval

Authors:
Hsin-Hsi Chen;Guo-Wei Bian;Wen-Cheng Lin
Affiliations:
National Taiwan University, Taipei, Taiwan, R. O. C.;National Taiwan University, Taipei, Taiwan, R. O. C.;National Taiwan University, Taipei, Taiwan, R. O. C.
Venue:
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Year:
1999

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Abstract

This paper deals with translation ambiguity and target polysemy problems together. Two monolingual balanced corpora are employed to learn word co-occurrence for translation ambiguity resolution, and augmented translation restrictions for target polysemy resolution. Experiments show that the model achieves 62.92% of monolingual information retrieval, and is 40.80% addition to the select-all model. Combining the target polysemy resolution, the retrieval performance is about 10.11% increase to the model resolving translation ambiguity only.