Abstract
Performance prediction has gained increasing attention in the IR field since the half of the past decade and has become an established research topic in the field. The present work restates the problem in the subarea of Collaborative Filtering (CF), where it has barely been researched so far. We investigate the adaptation of clarity-based query performance predictors to define predictors of neighbor performance in CF. The proposed predictors are introduced in a memory-based CF algorithm to produce a dynamic variant where neighbor ratings are weighted based on their predicted performance. The approach is tested with encouraging empirical results, as the dynamic variants consistently outperform the baseline algorithms, with increasing difference on small neighborhoods.
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References
Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005)
Amati, G., Carpineto, C., Romano, G.: Query difficulty, robustness, and selective application of query expansion. In: McDonald, S., Tait, J.I. (eds.) ECIR 2004. LNCS, vol. 2997, pp. 127–137. Springer, Heidelberg (2004)
Aslam, J.A., Pavlu, V.: Query hardness estimation using Jensen-Shannon divergence among multiple scoring functions. In: Amati, G., Carpineto, C., Romano, G. (eds.) ECiR 2007. LNCS, vol. 4425, pp. 198–209. Springer, Heidelberg (2007)
Baltrunas, L., Ricci, F.: Locally adaptive neighborhood selection for collaborative filtering recommendations. In: Nejdl, W., Kay, J., Pu, P., Herder, E. (eds.) AH 2008. LNCS, vol. 5149, pp. 22–31. Springer, Heidelberg (2008)
Carmel, D., Yom-Tov, E., Darlow, A., Pelleg, D.: What makes a query difficult? In: 29th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2006), pp. 390–397. ACM Press, New York (2006)
Cronen-Townsend, S., Zhou, Y., Croft, W.: Precision prediction based on ranked list coherence. Information Retrieval 9(6), 723–755 (2006)
Cronen-Townsend, S., Zhou, Y., Croft, B.W.: Predicting query performance. In: 25th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2002), pp. 299–306. ACM Press, New York (2002)
Diaz, F., Jones, R.: Using temporal profiles of queries for precision prediction. In: 27th annual international conference on Research and development in information retrieval (SIGIR 2004), pp. 18–24. ACM Press, New York (2004)
Goldberg, K., Roeder, T., Gupta, D., Perkins, C.: Eigentaste: A constant time collaborative filtering algorithm. Information Retrieval 4(2), 133–151 (2001)
Hauff, C., Hiemstra, D., de Jong, F.: A survey of pre-retrieval query performance predictors. In: 17th ACM conference on Information and knowledge management (CIKM 2008), pp. 1419–1420. ACM Press, New York (2008)
He, B., Ounis, I.: Inferring query performance using pre-retrieval predictors. In: Apostolico, A., Melucci, M. (eds.)String Processing and Information Retrieval. LNCS, vol. 2346, pp. 43–54. Springer, Heidelberg (2004)
Herlocker, J., Konstan, J.A., Riedl, J.: An empirical analysis of design choices in neighborhood-based collaborative filtering algorithms. Information Retrieval 5(4), 287–310 (2002)
Jensen, E.C., Beitzel, S.M., Grossman, D., Frieder, O., Chowdhury, A.: Predicting query difficulty on the web by learning visual clues. In: 28th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2005), pp. 615–616. ACM Press, New York (2005)
Jones, K.S.: A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation 28(1), 11–20 (1972)
Kwon, K., Cho, J., Park, Y.: Multidimensional credibility model for neighbor selection in collaborative recommendation. Expert Systems with Applications 36(3), 7114–7122 (2009)
Lavrenko, V., Allan, J., Deguzman, E., Laflamme, D., Pollard, V., Thomas, S.: Relevance models for topic detection and tracking. In: 2nd international conference on Human Language Technology Research (HLT 2002), pp. 115–121. Morgan Kaufmann Publishers Inc., San Francisco (2002)
Macdonald, C., He, B., Ounis, I.: Predicting query performance in intranet search. In: ACM SIGIR Workshop on Predicting Query Difficulty – Methods and Applications, Salvador, Brazil (2005)
Mothe, J., Tanguy, L.: Linguistic features to predict query difficulty. In: ACM SIGIR Workshop on Predicting Query Difficulty – Methods and Applications, Salvador, Brazil (2005)
Plachouras, V., He, B., Ounis, I.: University of Glasgow at TREC2004: Experiments in Web, Robust and Terabyte tracks with Terrier. In: 13th Text Retrieval Conference (TREC 2004), Gaithesburg, Maryland (2004)
Wang, J., de Vries, A.P., Reinders, M.J.T.: Unifying user-based and item-based collaborative filtering approaches by similarity fusion. In: 29th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2006), pp. 501–508. ACM Press, New York (2006)
Xue, G.R., Lin, C., Yang, Q., Xi, W., Zeng, H.J., Yu, Y., Chen, Z.: Scalable collaborative filtering using cluster-based smoothing. In: 28th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2005), pp. 114–121. ACM Press, New York (2005)
Yom-Tov, E., Fine, S., Carmel, D., Darlow, A.: Learning to estimate query difficulty: including applications to missing content detection and distributed information retrieval. In: 28th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2005), pp. 512–519. ACM Press, New York (2005)
Zhou, Y., Croft, B.W.: Ranking robustness: a novel framework to predict query performance. In: 15th ACM conference on Information and knowledge management (CIKM 2006), pp. 567–574. ACM Press, New York (2006)
Zhou, Y., Croft, B.W.: Query performance prediction in web search environments. In: 30th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2007), pp. 543–550. ACM Press, New York (2007)
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Bellogín, A., Castells, P. (2009). Predicting Neighbor Goodness in Collaborative Filtering. In: Andreasen, T., Yager, R.R., Bulskov, H., Christiansen, H., Larsen, H.L. (eds) Flexible Query Answering Systems. FQAS 2009. Lecture Notes in Computer Science(), vol 5822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04957-6_52
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DOI: https://doi.org/10.1007/978-3-642-04957-6_52
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