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A Comparative Study of Query and Document Translation for Cross-Language Information Retrieval

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Machine Translation and the Information Soup (AMTA 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1529))

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Abstract

Cross-language retrieval systems use queries in one natural language to guide retrieval of documents that might be written in another. Acquisition and representation of translation knowledge plays a central role in this process. This paper explores the utility of two sources of translation knowledge for cross-language retrieval. We have implemented six query translation techniques that use bilingual term lists and one based on direct use of the translation output from an existing machine translation system; these are compared with a document translation technique that uses output from the same machine translation system. Average precision measures on a TREC collection suggest that arbitrarily selecting a single dictionary translation is typically no less effective than using every translation in the dictionary, that query translation using a machine translation system can achieve somewhat better effectiveness than simpler techniques, and that document translation may result in further improvements in retrieval effectiveness under some conditions.

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References

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© 1998 Springer-Verlag Berlin Heidelberg

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Oard, D.W. (1998). A Comparative Study of Query and Document Translation for Cross-Language Information Retrieval. In: Farwell, D., Gerber, L., Hovy, E. (eds) Machine Translation and the Information Soup. AMTA 1998. Lecture Notes in Computer Science(), vol 1529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49478-2_42

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  • DOI: https://doi.org/10.1007/3-540-49478-2_42

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65259-5

  • Online ISBN: 978-3-540-49478-2

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