Abstract
Query translation is the mainstream in cross-language information retrieval, but ambiguity must be resolved by methods based on dictionary translation. In this paper, we propose a progressive algorithm for disambiguation which is derived from another algorithm we propose called the max-sum model. The new algorithm take a strategy called weighted-average probability distribution to redistribute the probabilities. Moreover, the new algorithm can be computed in a more direct way by solving an equation system. All the resource our method requires is a bilingual dictionary and a monolingual corpus. Experiments show it outperforms four other methods.
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Yuan, S.A., Yu, S.N. (2008). A Progressive Algorithm for Cross-Language Information Retrieval Based on Dictionary Translation. In: Li, H., Liu, T., Ma, WY., Sakai, T., Wong, KF., Zhou, G. (eds) Information Retrieval Technology. AIRS 2008. Lecture Notes in Computer Science, vol 4993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68636-1_24
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DOI: https://doi.org/10.1007/978-3-540-68636-1_24
Publisher Name: Springer, Berlin, Heidelberg
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