Presentation 2009-06-19
Efficient Approximate Nearest Neighbor Search Based on Accessing Neighboring Buckets
Tomoyuki MUTO, Masashi TADA, Masakazu IWAMURA, Koichi KISE,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Approximate nearest neighbor search is a technique which greatly reduces processing time and required amount of memory for nearest neighbor search. Further reduction of required amount of memory of the approximate nearest neighbor search is an important task. In this paper, we model a method to access neighboring buckets used in [7], [8], and reveal the method requires less amount of memory than LSH by an experiment and analysis.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Approximate nearest neighbor search / Locality Sensitive Hashing / Accessing Neighboring Buckets
Paper # PRMU2009-53
Date of Issue

Conference Information
Committee PRMU
Conference Date 2009/6/11(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Efficient Approximate Nearest Neighbor Search Based on Accessing Neighboring Buckets
Sub Title (in English)
Keyword(1) Approximate nearest neighbor search
Keyword(2) Locality Sensitive Hashing
Keyword(3) Accessing Neighboring Buckets
1st Author's Name Tomoyuki MUTO
1st Author's Affiliation Graduate School of Engineering, Osaka Prefecture University()
2nd Author's Name Masashi TADA
2nd Author's Affiliation Graduate School of Engineering, Osaka Prefecture University
3rd Author's Name Masakazu IWAMURA
3rd Author's Affiliation Graduate School of Engineering, Osaka Prefecture University
4th Author's Name Koichi KISE
4th Author's Affiliation Graduate School of Engineering, Osaka Prefecture University
Date 2009-06-19
Paper # PRMU2009-53
Volume (vol) vol.109
Number (no) 88
Page pp.pp.-
#Pages 6
Date of Issue