Abstract
We present in this paper well-founded cross-language extensions of the recently introduced models in the information-based family for information retrieval, namely the LL (log-logistic) and SPL (smoothed power law) models of [4]. These extensions are based on (a) a generalization of the notion of information used in the information-based family, (b) a generalization of the random variables also used in this family, and (c) the direct expansion of query terms with their translations. We then review these extensions from a theoretical point-of-view, prior to assessing them experimentally. The results of the experimental comparisons between these extensions and existing CLIR systems, on three collections and three language pairs, reveal that the cross-language extension of the LL model provides a state-of-the-art CLIR system, yielding the best performance overall.
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Li, B., Gaussier, E. (2012). An Information-Based Cross-Language Information Retrieval Model. In: Baeza-Yates, R., et al. Advances in Information Retrieval. ECIR 2012. Lecture Notes in Computer Science, vol 7224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28997-2_24
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DOI: https://doi.org/10.1007/978-3-642-28997-2_24
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