Clustering-based Retrieval
Clustering-Based Retrieval is a vector space retrieval method that organizes documents into clusters based on similarity metrics, and retrieves relevant results by identifying the cluster most closely associated with the query vector.
299
Publications
19.2K
Citations
693
Authors
301
Institutions
Publications per year
2017–2026
28
Parents
299
Douglass R. Cutting, David R. Karger, Jan Pedersen et al. · ACM SIGIR Forum · 2017 · 1.4K citations
Oren Zamir, Oren Etzioni · 1998 · 1.1K citations
Scatter/Gather: a cluster-based approach to browsing large document collections
Douglass R. Cutting, David R. Karger, Jan Pedersen et al. · 1992 · 947 citations · Full text
Agglomerative clustering of a search engine query log
Doug Beeferman, Adam Berger · 2000 · 772 citations · Full text
Grouper: a dynamic clustering interface to Web search results
Oren Zamir, Oren Etzioni · Computer Networks · 1999 · 717 citations
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Technion – Israel Institute of Technology
Haifa, Israel
10 h-index
15 publications
824 citations
Microsoft Research Asia (China)
Beijing, China
7 h-index
25 publications
2.6K citations
Tsinghua University
Beijing, China
6 h-index
9 publications
306 citations

Cornell University
Ithaca, United States
6 h-index
10 publications
880 citations
Stanford University
Stanford, United States
6 h-index
11 publications
4.6K citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
17 publications
1.5K citations

University of Massachusetts Amherst
Amherst Center, United States
6 h-index
9 publications
1.3K citations
University of Illinois Chicago
Chicago, United States
5 h-index
9 publications
332 citations
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14 publications · 622 citations
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JASIS · 7 publications · 398 citations
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TODS · 4 publications · 273 citations
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4 publications · 159 citations
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4 publications · 78 citations
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