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Mining rich session context to improve web search

Guangyu Zhu, Gilad Mishne
2009 Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '09  
In this paper, we expand the use of browsing information for web search ranking and other applications, with an emphasis on analyzing individual user sessions for creating aggregate models.  ...  Finally, we discuss novel applications of ClickRank in providing enriched user web search experience, highlighting the usefulness of our approach for non-ranking tasks.  ...  ACKNOWLEDGMENTS We thank Benoit Dumoulin and other members of the Query Intent Modeling Team in Yahoo! Search and Yahoo! Research Barcelona for useful discussions.  ... 
doi:10.1145/1557019.1557131 dblp:conf/kdd/ZhuM09 fatcat:6se74mfubfb3lix6unbrnlg2ba

Web Search and Browse Log Mining: Challenges, Methods, and Applications [chapter]

Daxin Jiang
2011 Lecture Notes in Computer Science  
Smoothing clickthrough data for web search ranking.  ...  Search Learning Pair-wise Preference Search Results Clustering Sequential Click Models Personalized Search Search System Monitoring & Feedback Search engine metrics User satisfaction evaluation  ...  Mining rich session context to improve web search. KDD'09.  ... 
doi:10.1007/978-3-642-20152-3_42 fatcat:r23eolebifbqrdrx4lnnfrnkha

Mining search and browse logs for web search

Daxin Jiang, Jian Pei, Hang Li
2013 ACM Transactions on Intelligent Systems and Technology  
Acknowledgement We sincerely thank the anonymous reviewers for their insightful and constructive comments and suggestions, which help to improve the quality of this article.  ...  To enhance the accuracy of classification, and proposed to use the search results of a query at web search engines to enrich the original query and use the enrichment of the query in classification.  ...  Zhu and Mishne [2009] viewed a session as a sequence of hops through the web graph by a user, and computed ClickRank as the importance of each web page in the session.  ... 
doi:10.1145/2508037.2508038 fatcat:rfysu5bx7vaabgd4jyms2wyyta

Social Search [chapter]

Peter Brusilovsky, Barry Smyth, Bracha Shapira
2018 Lecture Notes in Computer Science  
Modern web search engines have evolved from their roots in information retrieval to developing new ways to cope with the unique nature of web search.  ...  In this chapter, we review recent research that aims to make search a more social activity by combining readily available social signals with various strategies for using these signals to influence or  ...  Once learned from data, click models can produce a data-informed ranking of web pages for a given query. The idea of learning a model of user search behavior was introduced by Agichtein et al. [6] .  ... 
doi:10.1007/978-3-319-90092-6_7 fatcat:ro6hjgwhgvgwrncakrpfv5brye

Contextual Search: A Computational Framework

Massimo Melucci
2012 Foundations and Trends in Information Retrieval  
Therefore, in this survey, we describe how statistical models can process contextual variables to infer the contextual factors underlying the current search context.  ...  Information Retrieval (IR) to design systems which can effectively and efficiently constrain search within the boundaries given by context, thus transforming classical search into contextual search.  ...  Sebastiani for inviting me to write this survey; Doug Oard for his great patience and encouragement; and three anonymous reviewers for their careful and thoughtful comments.  ... 
doi:10.1561/1500000023 fatcat:bjx5it7en5fapbg6fvbqs6e7jy