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Download Advances in Information Retrieval: 29th European Conference by Andrei Broder (auth.), Giambattista Amati, Claudio PDF

By Andrei Broder (auth.), Giambattista Amati, Claudio Carpineto, Giovanni Romano (eds.)

ISBN-10: 3540714944

ISBN-13: 9783540714941

ISBN-10: 3540714960

ISBN-13: 9783540714965

This booklet constitutes the refereed complaints of the twenty ninth annual eu convention on info Retrieval study, ECIR 2007, held in Rome, Italy in April 2007. The forty two revised complete papers and 19 revised brief papers awarded including three keynote talks and 21 poster papers have been rigorously reviewed and chosen from 220 article submissions and seventy two poster paper submissions. The papers are geared up in topical sections on conception and layout, potency, peer-to-peer networks, end result merging, queries, relevance suggestions, evaluate, type and clustering, filtering, subject id, professional discovering, XML IR, net IR, and multimedia IR.

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Extra resources for Advances in Information Retrieval: 29th European Conference on IR Research, ECIR 2007, Rome, Italy, April 2-5, 2007. Proceedings

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And Zobel, J. Similarity measures for tracking information flow. In Proceedings of CIKM ‘05, pages 517-524, 2005. [8] Murdock, V. B. A Translation Model for Sentence Retrieval. In Proceedings of HLT/EMNLP ‘05, pages 684-691, 2005. [9] Porter, M. F. An algorithm for suffix stripping. Program, 14(3), pages 130-137, 1980. [10] Rocchio, J. J. Relevance Feedback in Information Retrieval, pages 313-323. PrenticeHall, 1971. [11] Sahami, M. and Heilman, T. A web-based kernel function for measuring the similarity of short text snippets.

Indeed, preliminary experimentation with ML2 has shown that using Stirling’s formula affects the performance of the weighting model, due to the accumulation of the approximation error from computing the factorial k + 2 times (k is the number of fields). This is not the case for the Poisson-based weighting models PL2 and PL2F, where there is only one factorial computation for each query term (see Equation (2)). Hence, the computation of factorials in Equation (8) is performed using the approximation of Lanczos to the Γ function.

Our deduplication policy states that we keep the highest ranked match and remove all others. Although this combination scheme is naïve, it has the advantage that there are no combination parameters to learn. 4 Summary of Methods Evaluated Table 1 summarizes the methods we evaluate in the next section. For each method, we include the query and candidate representations and the similarity measure used. The Lexical method, which considers the surface forms of the query and candidate, makes use of a hybrid technique that ranks exact matches first, then phrase matches, and finally subset matches.

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