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  • The pivot tables are a popular metric access method, primarily designed as a main-memory index structure. It has been many times proven that pivot tables are very efficient in terms of distance computations, hence, when assuming a computationally expensive distance function. However, for cheaper distance functions and/or huge datasets exceeding the capacity of the main memory, the classic pivot tables become inefficient. In this paper, we propose a persistent variant of pivot tables, the clustered pivot tables, focusing on minimizing I/O cost when accessing small data blocks (a few kilobytes). The clustered pivot tables employs a preprocessing method utilizing the M-tree in the role of clustering technique and an original heuristic for I/O-optimized kNN query processing. In the experiments we empirically show that our proposed method significantly reduces the number of necessary I/O operations during query processing.
  • The pivot tables are a popular metric access method, primarily designed as a main-memory index structure. It has been many times proven that pivot tables are very efficient in terms of distance computations, hence, when assuming a computationally expensive distance function. However, for cheaper distance functions and/or huge datasets exceeding the capacity of the main memory, the classic pivot tables become inefficient. In this paper, we propose a persistent variant of pivot tables, the clustered pivot tables, focusing on minimizing I/O cost when accessing small data blocks (a few kilobytes). The clustered pivot tables employs a preprocessing method utilizing the M-tree in the role of clustering technique and an original heuristic for I/O-optimized kNN query processing. In the experiments we empirically show that our proposed method significantly reduces the number of necessary I/O operations during query processing. (en)
Title
  • Clustered Pivot Tables for I/O-optimized Similarity Search
  • Clustered Pivot Tables for I/O-optimized Similarity Search (en)
skos:prefLabel
  • Clustered Pivot Tables for I/O-optimized Similarity Search
  • Clustered Pivot Tables for I/O-optimized Similarity Search (en)
skos:notation
  • RIV/00216208:11320/11:10099618!RIV12-GA0-11320___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GAP202/11/0968)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 190682
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/11:10099618
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Similarity Search; I/O-optimized; Pivot Tables; Clustering (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [A4CDB8D3C397]
http://linked.open...v/mistoKonaniAkce
  • Lipari, Italy
http://linked.open...i/riv/mistoVydani
  • New York, USA
http://linked.open...i/riv/nazevZdroje
  • Fourth International Conference on Similarity Search and Applications 2011
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Lokoč, Jakub
  • Moško, Juraj
  • Skopal, Tomáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://bibframe.org/vocab/doi
  • 10.1145/1995412.1995418
http://purl.org/ne...btex#hasPublisher
  • ACM
https://schema.org/isbn
  • 978-1-4503-0795-6
http://localhost/t...ganizacniJednotka
  • 11320
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