By ChengXiang Zhai (auth.), Giambattista Amati, Fabio Crestani (eds.)
This publication constitutes the refereed court cases of the 3rd foreign convention at the idea of data Retrieval, ICTIR 2011, held in Bertinoro, Italy, in September 2011. The 25 revised complete papers and thirteen brief papers provided including the abstracts of 2 invited talks have been rigorously reviewed and chosen from sixty five submissions. The papers hide themes starting from question enlargement, co-occurence research, consumer and interactive modelling, procedure functionality prediction and comparability, and probabilistic techniques for rating and modelling IR to subject matters with regards to interdisciplinary techniques or purposes. they're prepared into the subsequent topical sections: predicting question functionality; latent semantic research and notice co-occurrence research; question enlargement and re-ranking; comparability of data retrieval structures and approximate seek; likelihood rating precept and choices; interdisciplinary methods; consumer and relevance; end result diversification and question disambiguation; and logical operators and descriptive approaches.
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Extra resources for Advances in Information Retrieval Theory: Third International Conference, ICTIR 2011, Bertinoro, Italy, September 12-14, 2011. Proceedings
In particular, the approaches based on Information Theory principles and measures, as developed in the query clarity models, have shown to be useful in many ways to deal effectively with poorly-performing queries . We propose different vocabulary spaces where clarity definition may be applied to, in order to better capture the ambiguity in user preferences. Moreover, we define alternative statistical models and estimating approaches, under different independence assumptions. In conducted experiments, we have obtained similar correlation values to those of stateof-the-art predictors in terms of average correlation.
They implement an item-based CF approach with different normalization and weighting functions for the similarity or rating values. Finally, we implemented a content-based recommender (denoted as CBF) using movie genre, director, and country, from IMDb3, as item attributes. Table 4 shows the Pearson’s correlation values between the predictors presented in previous sections, and the nDCG when only the top 50 items are considered (nDCG@50). We can observe fairly high correlation values for recommenders TF-L1 and TF-L2, comparable to results in the query performance literature.
ACM Press, New York (2002) 7. : A framework for selective query expansion. In: 13th ACM Conference on Information and Knowledge Management, pp. 236–237. ACM Press, New York (2004) 8. : Learning to rank query reformulations. In: 33rd ACM Conference on Research and Development in Information Retrieval, pp. 807–808. ACM Press, New York (2010) 9. : Predicting the Effectiveness of Queries and Retrieval Systems. PhD thesis, University of Twente, Enschede (2010) 10. : A Survey of Pre-Retrieval Query Performance Predictors.
Advances in Information Retrieval Theory: Third International Conference, ICTIR 2011, Bertinoro, Italy, September 12-14, 2011. Proceedings by ChengXiang Zhai (auth.), Giambattista Amati, Fabio Crestani (eds.)