Interest Modeling is a computational framework within information filtering that characterizes individual user preferences by identifying and representing distinctive patterns of relevance from user interactions, thereby enabling personalized content selection.
351
Publications
20.3K
Citations
1K
Authors
374
Institutions
Publications per year
2017–2026
132
Parents
Publications
351
Xindong Wu, Xingquan Zhu, Gongqing Wu et al. · IEEE Transactions on Knowledge and Data Engineering · 2013 · 2.4K citations
Personalized news recommendation based on click behavior
Jiahui Liu, P. Dolan, Elin Rønby Pedersen · 2010 · 764 citations
Clustering Methods for Collaborative Filtering
Lyle Ungar, Dean P. Foster · 1998 · 630 citations
1–5 of 351
Authors
1K
- FW
7
h-index
- CW
7
h-index
- YH
7
h-index
- TQ
6
h-index
- SJ
5
h-index
1–5 of 1K
Institutions
374
Tsinghua University
Beijing, China
13 h-index
45 publications
2.1K citations
Chinese Academy of Sciences
Beijing, China
10 h-index
22 publications
940 citations
Microsoft (United States)
Redmond, United States
9 h-index
18 publications
3.1K citations
Texas A&M University
College Station, United States
9 h-index
30 publications
1.4K citations
Microsoft Research Asia (China)
Beijing, China
9 h-index
16 publications
955 citations
Alibaba Group (China)
Hangzhou, China
8 h-index
32 publications
2K citations
National University of Singapore
Singapore, Singapore
7 h-index
17 publications
3.2K citations
University of California, Irvine
Irvine, United States
6 h-index
12 publications
835 citations
1–8 of 374
Venues
- Expert Systems with Applications
7 publications · 511 citations
7
h-index
- Proceedings of the AAAI Conference on Artificial Intelligence
Conference · 7 publications · 1.3K citations
7
h-index
- Knowledge-Based Systems
6 publications · 288 citations
6
h-index
- ACM Transactions on Information Systems
5 publications · 588 citations
5
h-index
- Journal of the American Society for Information Science and Technology
JASIST · 5 publications · 184 citations
5
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1–5