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  • Periodic Data, Burden or Convenience

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    91672_1.pdf (161.6Kb)
    Author(s)
    Stantic, Bela
    Griffith University Author(s)
    Stantic, Bela
    Year published
    2013
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    Abstract
    Periodic events seem to be an intrinsic part of our life, and a way of perceiving reality. There are many application domains where periodic data play a major role. In many of such domains, the huge number of repetitions make the goal of explicitly storing and accessing such data very challenging to the extent of even not being possible, in cases of open ended intervals. In this work, we present a concept to represent periodic data in an implicit way. The representation model we propose captures the notion of periodic granularity provided by the temporal database glossary. We define the algebraic operators, and introduce ...
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    Periodic events seem to be an intrinsic part of our life, and a way of perceiving reality. There are many application domains where periodic data play a major role. In many of such domains, the huge number of repetitions make the goal of explicitly storing and accessing such data very challenging to the extent of even not being possible, in cases of open ended intervals. In this work, we present a concept to represent periodic data in an implicit way. The representation model we propose captures the notion of periodic granularity provided by the temporal database glossary. We define the algebraic operators, and introduce access algorithms to cope with them and also with temporal range queries, proving that they are correct and complete with respect to the traditional explicit approach. In an experimental evaluation we show the advantages of our approach with respect to traditional explicit approach, in terms of space usage, physical disk I/O's and query response time.
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    Conference Title
    Advances in Databases and Information Systems 17th East European Conference, ADBIS 2013 Genoa, Italy, September 1-4, 2013 Proceedings
    Publisher URI
    http://adbis2013.disi.unige.it/
    DOI
    https://doi.org/10.1007/978-3-642-40683-6_3
    Copyright Statement
    © 2013 Springer-Verlag Berlin Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
    Subject
    Data Structures
    Artificial Intelligence and Image Processing not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/59671
    Collection
    • Conference outputs

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