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19 December 2001 Angle-Tree: a new index structure for high-dimensional point data
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Proceedings Volume 4676, Storage and Retrieval for Media Databases 2002; (2001) https://doi.org/10.1117/12.451114
Event: Electronic Imaging, 2002, San Jose, California, United States
Abstract
Many multi-dimensional index structures, such as R-Tree, R*-Tree, X-Tree, SS-Tree, VA-File, etc. have been proposed to support similarity search with l1, l2 or l(infinity ) distance as similarity measure. But they can not support such similarity search with cosine as the similarity measure. In this paper, an index structure Angle-Tree is introduced to resolve the problem. It first projects all the high dimensional points onto the unit hyper-spherical surface, i.e. normalize each original vector in the database into a unit one. Then an index structure similar to R-Tree is built for those projected points. The experimental results show that the Angle-Tree can decrease the cost of disk I/O and support fast similarity search.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daoguo Dong, Xiangyang Xue, Hangzai Luo, and Yingqiang Lin "Angle-Tree: a new index structure for high-dimensional point data", Proc. SPIE 4676, Storage and Retrieval for Media Databases 2002, (19 December 2001); https://doi.org/10.1117/12.451114
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