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On Top-k Search with No Random Access Using Small Memory

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Advances in Databases and Information Systems (ADBIS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5207))

Abstract

Methods of top-k search with no random access can be used to find k best objects using sorted lists of attributes that can be read only by sorted access. Such methods usually need to work with a large number of candidates during the computation. In this paper we propose new methods of no random access top-k search that can be used to compute k best objects using small memory. We present results of experiments showing improvement in speed depending on ratio of memory size and data size. Our system outperforms other also when the total number of attributes is much bigger than number of query attributes (varying with user).

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Authors and Affiliations

  1. University of P.J.Šafárik, Košice, Slovakia

    Peter Gurský

  2. Charles University, Prague, Czech Republic

    Peter Vojtáš

Authors
  1. Peter Gurský
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  2. Peter Vojtáš
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Paolo Atzeni Albertas Caplinskas Hannu Jaakkola

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© 2008 Springer-Verlag Berlin Heidelberg

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Gurský, P., Vojtáš, P. (2008). On Top-k Search with No Random Access Using Small Memory. In: Atzeni, P., Caplinskas, A., Jaakkola, H. (eds) Advances in Databases and Information Systems. ADBIS 2008. Lecture Notes in Computer Science, vol 5207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85713-6_8

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  • DOI: https://doi.org/10.1007/978-3-540-85713-6_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85712-9

  • Online ISBN: 978-3-540-85713-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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