Personalized Search is an information retrieval approach that adapts the retrieval and ranking of search results to an individual user by exploiting a user model derived from that user’s preferences, behavior, and context, rather than applying a uniform ranking to all users.
1.3K
Publications
70.2K
Citations
3.1K
Authors
864
Institutions
Publications per year
2017–2026
294
Parents
Publications
1.3K
1–5 of 1.3K
Authors
3.1K
- JW
19
h-index
- ZD
16
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- RW
16
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- SD
16
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- MD
14
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1–5 of 3.1K
Institutions
864
Microsoft (United States)
Redmond, United States
41 h-index
149 publications
18.9K citations
Microsoft Research Asia (China)
Beijing, China
22 h-index
65 publications
5.3K citations
Renmin University of China
Beijing, China
21 h-index
77 publications
2.8K citations
Hong Kong University of Science and Technology
Hong Kong, Hong Kong
18 h-index
56 publications
3.1K citations
Tsinghua University
Beijing, China
18 h-index
48 publications
2.9K citations
Google (United States)
Mountain View, United States
16 h-index
75 publications
8.2K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
16 h-index
60 publications
2.6K citations
University of Amsterdam
Amsterdam, The Netherlands
15 h-index
39 publications
1.8K citations
1–8 of 864
Venues
- IEEE Transactions on Knowledge and Data Engineering
TKDE · 18 publications · 1.2K citations
17
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- arXiv (Cornell University)
Repository · 22 publications · 1.1K citations
16
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- Information Processing & Management
14 publications · 606 citations
13
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- Knowledge-Based Systems
12 publications · 315 citations
11
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- ACM Transactions on Information Systems
11 publications · 713 citations
11
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