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Indexing and Searching for Reduced-Dimensional Vectors  

Jeong, Seung-Do (한양사이버대하교 정보통신공학과)
Kim, Sang-Wook (한양대학교 컴퓨터공학부)
Choi, Byung-Uk (한양대학교 컴퓨터공학부)
Abstract
In this paper, we first address the problems associated with indexing and searching for reduced-dimensional vectors, which are reduced by using a combination of angle approximation and dimension grouping. Then, we propose a novel method to solve the problems. We also show the superiority of the proposed method by performing extensive experiments with synthetic and real-life data sets.
Keywords
Multimedia Information Retrieval; Multi-dimensional Indexing; Query Processing; Dimensionality Reduction;
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