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SIGMOD
2011
ACM

Effective data co-reduction for multimedia similarity search

7 years 9 months ago
Effective data co-reduction for multimedia similarity search
Multimedia similarity search has been playing a critical role in many novel applications. Typically, multimedia objects are described by high-dimensional feature vectors (or points) which are organized in databases for retrieval. Although many high-dimensional indexing methods have been proposed to facilitate the search process, efficient retrieval over large, sparse and extremely high-dimensional databases remains challenging due to the continuous increases in data size and feature dimensionality. In this paper, we propose the first framework for Data Co-Reduction (DCR) on both data size and feature dimensionality. By utilizing recently developed co-clustering methods, DCR simultaneously reduces both size and dimensionality of the original data into a compact subspace, where lower bounds of the actual distances in the original space can be efficiently established to achieve fast and lossless similarity search in the filter-andrefine approach. Particularly, DCR considers the dualit...
Zi Huang, Heng Tao Shen, Jiajun Liu, Xiaofang Zhou
Added 17 Sep 2011
Updated 17 Sep 2011
Type Journal
Year 2011
Where SIGMOD
Authors Zi Huang, Heng Tao Shen, Jiajun Liu, Xiaofang Zhou
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