Session-based Search
Session-Based Search is a web search paradigm that models user information needs within discrete interaction sequences, distinguishing itself by leveraging temporal user behavior patterns and query-context dependencies from a single browsing session to personalize and refine search results.
80
Publications
4.2K
Citations
210
Authors
85
Institutions
Publications per year
2017–2026
26
80
Real life information retrieval: a study of user queries on the Web
Bernard J. Jansen, Amanda Spink, Judy Bateman et al. · ACM SIGIR Forum · 1998 · 621 citations · Full text
Modeling the impact of short- and long-term behavior on search personalization
Paul N. Bennett, Ryen W. White, Wei Chu et al. · 2012 · 297 citations
Search Personalization Using Machine Learning
Hema Yoganarasimhan · Management Science · 2019 · 159 citations
Reinforcement Learning to Rank in E-Commerce Search Engine
Yujing Hu, Qing Da, Anxiang Zeng et al. · 2018 · 148 citations
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Microsoft (United States)
Redmond, United States
9 h-index
28 publications
3.5K citations
Georgetown University
Washington, United States
7 h-index
17 publications
490 citations

University of Amsterdam
Amsterdam, The Netherlands
7 h-index
16 publications
572 citations

Renmin University of China
Beijing, China
6 h-index
14 publications
222 citations
Tsinghua University
Beijing, China
5 h-index
23 publications
533 citations
University College London
London, United Kingdom
5 h-index
7 publications
138 citations
Amsterdam University of the Arts
Amsterdam, The Netherlands
4 h-index
12 publications
383 citations
Yahoo (United States)
Sunnyvale, United States
3 h-index
12 publications
567 citations
1–8 of 85
4 publications · 110 citations
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TKDE · 3 publications · 134 citations
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2 publications · 61 citations
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2 publications · 29 citations
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Repository · 1 publications · 35 citations
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