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Empirical studies on the impact of lexical resources on CLIR performance
Ist Teil von
Information processing & management, 2005-05, Vol.41 (3), p.475-487
Ort / Verlag
Oxford: Elsevier Ltd
Erscheinungsjahr
2005
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
In this paper, we compile and review several experiments measuring cross-lingual information retrieval (CLIR) performance as a function of the following resources: bilingual term lists, parallel corpora, machine translation (MT), and stemmers. Our CLIR system uses a simple probabilistic language model; the studies used TREC test corpora over Chinese, Spanish and Arabic. Our findings include:
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One can achieve an acceptable CLIR performance using only a bilingual term list (70–80% on Chinese and Arabic corpora).
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However, if a bilingual term list and parallel corpora are available, CLIR performance can rival monolingual performance.
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If no parallel corpus is available, pseudo-parallel texts produced by an MT system can partially overcome the lack of parallel text.
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While stemming is useful normally, with a very large parallel corpus for Arabic–English, stemming hurt performance in our empirical studies with Arabic, a highly inflected language.