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Qcluster: Relevance Feedback Using Adaptive Clustering for Content-Based Image Retrieval

Summary: Qcluster introduces adaptive classification and cluster-merging for disjunctive, multi-cluster relevance feedback in large-scale image retrieval. It uses linear-transform invariant measures to make retrieval robust to cluster shapes, achieving significant gains over query expansion and query-point movement on MARS with fast convergence to the user’s true need. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3466
Venue
SIGMOD
Year
2003
Pagerank
4.4106026e-05
Overall Rank
9,003 | 37.37%
DOI
-

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Rank Citing Paper Year Venue Pagerank
6,130 VOCAL: Video Organization and Interactive Compositional AnaLytics 2022 CIDR 5.1962107e-05
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