Visualisation of Temporal Interval Association Rules

Chris P. Rainsford, John F. Roddick

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    16 Citations (Scopus)

    Abstract

    Temporal intervals and the interaction of interval-based events are fundamental in many domains including medicine, commerce, computer security and various types of normalcy analysis. In order to learn from temporal interval data we have developed a temporal interval association rule algorithm. In this paper, we will provide a definition for temporal interval association rules and present our visualisation techniques for viewing them. Visualisation techniques are particularly important because the complexity and volume of knowledge that is discovered during data mining often makes it difficult to comprehend. We adopt a circular graph for visualising a set of associations that allows underlying patterns in the associations to be identified. To visualize temporal relationships, a parallel coordinate graph for displaying the temporal relationships has been developed.

    Original languageEnglish
    Title of host publicationIDEAL '00
    Subtitle of host publicationProceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
    EditorsHelen Meng, Kwong Sak Leung, Lai-Wan Chan
    PublisherSpringer-Verlag
    Pages91-96
    Number of pages6
    ISBN (Print)3540414509, 9783540414506
    DOIs
    Publication statusPublished - Dec 2000
    Event2nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2000 - Shatin, N.T., Hong Kong
    Duration: 13 Dec 200015 Dec 2000

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume1983
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference2nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2000
    CountryHong Kong
    CityShatin, N.T.
    Period13/12/0015/12/00

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