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Pattern discovery in time-oriented data

Saraee, M, Theodoulidis , B and Koundourakis, G 1998, Pattern discovery in time-oriented data , in: International Conference on Advances in Pattern Recognition, 23-25 November 1998, Plymouth, England.

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    Abstract

    We present a data mining system, EasyMiner which has been developed for interactive mining of interesting patterns in time-oriented databases. This system implements a wide spectrum of data mining functions, including generalisation, characterisation, classification, association and relevant analysis. By enhancing several interesting data mining techniques, including attribute induction and association rule mining to handle time-oriented data the system provide a user friendly, interactive data mining environment with good performance. These algorithms were tested on time-oriented medical data and experimental results show that the algorithms are efficient and effective for discovery of pattern in databases.

    Item Type: Conference or Workshop Item (Paper)
    Themes: Media, Digital Technology and the Creative Economy
    Schools: Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre
    Journal or Publication Title: Proceedings of International Conference on Advances in Pattern Recognition: ICAPR
    Publisher: ICAPR
    Refereed: Yes
    Depositing User: Dr Mo Saraee
    Date Deposited: 27 Oct 2011 09:42
    Last Modified: 26 Aug 2013 23:09
    URI: http://usir.salford.ac.uk/id/eprint/18698

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