Approximate nearest neighbor searching in multimedia databases

H. Ferhatosmanoglu, E. Tuncel, D. Agrawal, A. El Abbadi

Research output: Contribution to conferencePaper

84 Citations (Scopus)

Abstract

In is paper, we develop a general framework for approximate nearest neighbor queries. We categorize the current approaches for nearest neighbor query processing based on either their ability to reduce the data set that needs to be examined, or their ability to reduce the representation size of each data object. We first propose modifications to well-known techniques to support the progressive processing of approximate nearest neighbor queries. A user may therefore stop the retrieval process once enough information has been returned. We then develop a new technique based on clustering that merges the benefits of the two general classes of approaches. Our cluster-based approach allows a user to progressively explore the approximate results with increasing accuracy. We propose a new metric for evaluation of approximate nearest neighbor searching techniques. Using both the proposed and the traditional metrics, we analyze and compare several techniques with a detailed perforrnance evaluation. We demonstrate the feasibility and efficiency of approximate nearest neighbor searching. We perform experiments on several real data sets and establish the superiority of the proposed cluster-based technique over the existing techniques for approximate nearest neighbor searching.

Original languageEnglish
Pages503-511
Number of pages9
Publication statusPublished - 1 Jan 2001
Event17th International Conference on Data Engineering - Heidelberg, Germany
Duration: 2 Apr 20016 Apr 2001

Other

Other17th International Conference on Data Engineering
CountryGermany
CityHeidelberg
Period2/4/016/4/01

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ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

Cite this

Ferhatosmanoglu, H., Tuncel, E., Agrawal, D., & El Abbadi, A. (2001). Approximate nearest neighbor searching in multimedia databases. 503-511. Paper presented at 17th International Conference on Data Engineering, Heidelberg, Germany.