Title
Boost Image Clustering With User Query Log
Keywords
Constrained clustering; Randomized contraction; Semi-supervised clustering; User query log
Abstract
Image clustering is to derive a salient grouping of images such that similar ones are placed in the same cluster, which is useful in many applications. In this paper, we propose a constrained clustering algorithm, which leverages the collected user query log to guide the clustering process. Our method models a set of images as a graph and randomly contracts two vertices into a meta vertex iteratively with regarding to their similarity until the desired number of image groups has been reached. The experimental results demonstrate the superiority of our proposal. © 2008 IEEE.
Publication Date
10-23-2008
Publication Title
2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings
Number of Pages
1241-1244
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ICME.2008.4607666
Copyright Status
Unknown
Socpus ID
54049110506 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/54049110506
STARS Citation
Cheng, Hao; Hua, Kien A.; and Yu, Ning, "Boost Image Clustering With User Query Log" (2008). Scopus Export 2000s. 9734.
https://stars.library.ucf.edu/scopus2000/9734