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An efficient algorithm for incremental mining of temporal association rules

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F10%3A86075424" target="_blank" >RIV/61989100:27240/10:86075424 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    An efficient algorithm for incremental mining of temporal association rules

  • Original language description

    This paper presents the concept of temporal association rules in order to solve the problem of handling time series by including time expressions into association rules. Actually, temporal databases are continually appended or updated so that the discovered rules need to be updated. Re-running the temporal mining algorithm every time is ineffective since it neglects the previously discovered rules, and repeats the work done previously. Furthermore, existing incremental mining techniques cannot deal withtemporal association rules. In this paper, an incremental algorithm to maintain the temporal association rules in a transaction database is proposed. The algorithm benefits from the results of earlier mining to derive the final mining output. The experimental results on both the synthetic and the real dataset illustrate a significant improvement over the conventional approach of mining the entire updated database. (C) 2010 Elsevier B.V. All rights reserved.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2010

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    DATA &amp; KNOWLEDGE ENGINEERING

  • ISSN

    0169-023X

  • e-ISSN

  • Volume of the periodical

    69

  • Issue of the periodical within the volume

    8

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    16

  • Pages from-to

  • UT code for WoS article

    000279596000004

  • EID of the result in the Scopus database