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The use of external text data in cross-language information retrieval based on machine translation

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1 Author(s)
T. Sakai ; Corp. Res. Dev. Center, Toshiba Corp., Kawasaki, Japan

This paper explores the use of an external (i.e. non-target) document collection in cross-language information retrieval (CLIR) based on machine translation (MT). In our CLIR and monolingual IR experiments using an external target language collection, we show that parallel pseudo-relevance feedback is comparable to collection enrichment. In our CLIR experiments using an external source language collection, we show that context-sensitive translation of pre-translation expansion terms outperforms word-by-word (or context-free) translation on average. Moreover, we show that the combination of context-sensitive translation with pseudo-relevance feedback significantly outperforms the corresponding context-free combination and the pseudo-relevance feedback component. Thus, context-sensitive translation for pre-translation expansion is probably superior to context-free translation.

Published in:

Systems, Man and Cybernetics, 2002 IEEE International Conference on  (Volume:6 )

Date of Conference:

6-9 Oct. 2002