ACM SIGMOD Anthology VLDB dblp.uni-trier.de

Fast High-Dimensional Data Search in Incomplete Databases.

Beng Chin Ooi, Cheng Hian Goh, Kian-Lee Tan: Fast High-Dimensional Data Search in Incomplete Databases. VLDB 1998: 357-367
@inproceedings{DBLP:conf/vldb/OoiGT98,
  author    = {Beng Chin Ooi and
               Cheng Hian Goh and
               Kian-Lee Tan},
  editor    = {Ashish Gupta and
               Oded Shmueli and
               Jennifer Widom},
  title     = {Fast High-Dimensional Data Search in Incomplete Databases},
  booktitle = {VLDB'98, Proceedings of 24rd International Conference on Very
               Large Data Bases, August 24-27, 1998, New York City, New York,
               USA},
  publisher = {Morgan Kaufmann},
  year      = {1998},
  isbn      = {1-55860-566-5},
  pages     = {357-367},
  ee        = {db/conf/vldb/OoiGT98.html},
  crossref  = {DBLP:conf/vldb/98},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

We propose and evaluate two indexing schemes for improving the efficiency of data retrieval in high-dimensional databases that are incomplete. These schemes are novel in that the search keys may contain missing attribute values. The first is a multi-dimensional index structure, called the Bitstring-augmented R-tree (BR-tree), whereas the second comprises a family of multipleone-dimensional one-attribute (MOSAIC) indexes. Our results show that both schemes can be superior over exhaustive search. Experimental results suggest that BR- trees have lower update and storage costs and are able to support range queries more efficiently under most circumstances, when compared to the MOSAIC indexing scheme. However, contrary to conventional wisdom, the MOSAIC structure outperformsthe BR-tree in retrieval time for point queries, as well as in range queries over incomplete databases for dimension-unrestricted data distributions.

Copyright © 1998 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.


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Ashish Gupta, Oded Shmueli, Jennifer Widom (Eds.): VLDB'98, Proceedings of 24rd International Conference on Very Large Data Bases, August 24-27, 1998, New York City, New York, USA. Morgan Kaufmann 1998, ISBN 1-55860-566-5
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Referenced by

  1. Cheng Hian Goh, Beng Chin Ooi, D. Sim, Kian-Lee Tan: GHOST: Fine Granularity Buffering of Indexes. VLDB 1999: 339-350
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