A cost model for incremental nearest neighbor search in multidimensional spaces

Yaokai Feng, Akifumi Makinouchi, Kunihiko Kaneko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Nearest Neighbor (NN) search has been widely used in spatial databases and multimedia databases. Incremental NN (INN) search is regarded as the optimal NN search because of the minimum number of node accesses and it can be used no matter whether the number of objects to be retrieved is fixed or not in advance. R*-tree is still regarded as being among the best high-dimensional indices. This paper presents an analytical model for estimating performance of the INN search algorithm on R*-tree. The theoretical analysis is verified by experiments.

Original languageEnglish
Title of host publicationProceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007
Pages111-116
Number of pages6
DOIs
Publication statusPublished - Dec 1 2007
Event2007 International Conference on Intelligent Pervasive Computing, IPC 2007 - Jeju Island, Korea, Republic of
Duration: Oct 11 2007Oct 13 2007

Publication series

NameProceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007

Other

Other2007 International Conference on Intelligent Pervasive Computing, IPC 2007
CountryKorea, Republic of
CityJeju Island
Period10/11/0710/13/07

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Computer Networks and Communications
  • Software

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  • Cite this

    Feng, Y., Makinouchi, A., & Kaneko, K. (2007). A cost model for incremental nearest neighbor search in multidimensional spaces. In Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007 (pp. 111-116). [4438406] (Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007). https://doi.org/10.1109/IPC.2007.20