Abstract
Aggregated search nowadays has become a widespread technique of generating Search Engine Result Page (SERP). The main task of aggregated search is incorporating results from a number of specialized search collections (often referenced as verticals) into a ranked list of Web-search results. To proceed with the blending algorithm one can use a variety of different sources of information starting from some textual features up to query-log data. In this paper we study the usefulness of personalized features for improving the quality of aggregated search ranking. The study is carried out by training a number of machine-learned blending algorithms, which differ by the sets of used features. Thus we not only measure the value of personalized approach in the aggregated search context, but also find out which classes of personalized features outperform the others.
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References
Arguello, J., Diaz, F., Callan, J.: Learning to aggregate vertical results into web search result. In: Proceedings of CIKM 2011(2011)
Arguello, J., Diaz, F., Callan, J., Crespo, J.F.: Sources of evidence for vertical selection. In: Proceedings of SIGIR 2009 (2009)
Arguello, J., Diaz, F., Paiement, J.F.: Vertical selection in the presence of unlabeled verticals. In: Proceedings of SIGIR 2010 (2010)
Bennett, P.N., Radlinski, F., White, R.W., Yilmaz, E.: Inferring and using location metadata to personalize web search. In: Proceedings of SIGIR 2011 (2011)
Bennett, P.N., White, R.W., Chu, W., Dumais, S.T., Bailey, P., Borisyuk, F., Cui, X.: Modeling the impact of short- and long-term behavior on search personalization. In: Proceedings of SIGIR 2012 (2012)
Collins-Thompson, K., Bennett, P.N., White, R.W., de la Chica, S., Sontag, D.: Personalizing web search results by reading level. In: Proceedings of CIKM 2011 (2011)
Diaz, F.: Integration of news content into web results. In: Proceedings of WSDM 2009 (2009)
Diaz, F., Arguello, J.: Adaptation of offline vertical selection predictions in the presence of user feedback. In: Proceedings of SIGIR 2009 (2009)
Dou, Z., Song, R., Wen, J.R.: A large-scale evaluation and analysis of personalized search strategies. In: Proceedings of WWW 2007 (2007)
Kharitonov, E., Serdyukov, P.: Gender-aware re-ranking. In: Proceedings of SIGIR 2012 (2012)
Ponnuswami, A., Pattabiraman, K., Wu, Q., Gilad-Bachrach, R., Kanungo, T.: On composition of a federated web search result page: using online users to provide pairwise preference for heterogeneous verticals. In: Proceedings of WSDM 2011 (2011)
Styskin, A., Romanenko, F., Vorobyev, F., Serdyukov, P.: Recency ranking by diversification of result set. In: Proceedings of CIKM 2011 (2011)
Vallet, D., Castells, P.: Personalized diversification of search results. In: Proceedings of SIGIR 2012 (2012)
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Makeev, S., Plakhov, A., Serdyukov, P. (2014). Personalizing Aggregated Search. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_17
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DOI: https://doi.org/10.1007/978-3-319-06028-6_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06027-9
Online ISBN: 978-3-319-06028-6
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