Knowledge acquisition from time series data through rough sets analysis

Yoshiyuki Matsumoto, Junzo Watada

    Research output: Contribution to journalArticle

    27 Citations (Scopus)

    Abstract

    Z. Pawlak proposed rough set theory in 1982. This theory provides a tool to mine knowledge as decision rules from a database, web-based information and so on. Decision rules are also used for data analysis. These decision rules can reason the conclusion of an unknown object using various premises. The objective of this paper is to apply the rough set theory to the analysis of time-series data. Using an example, this paper shows how knowledge is acquired and illustrates the difference among decision rules obtained using different time periods.

    Original languageEnglish
    Pages (from-to)4885-4897
    Number of pages13
    JournalInternational Journal of Innovative Computing, Information and Control
    Volume5
    Issue number12
    Publication statusPublished - 2009 Dec

    Fingerprint

    Rough set theory
    Knowledge Acquisition
    Knowledge acquisition
    Decision Rules
    Time Series Data
    Rough Set
    Time series
    Rough Set Theory
    Web-based
    Data analysis
    Unknown
    Knowledge

    Keywords

    • Knowledge acquisition
    • Rought sets
    • Time series data

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Information Systems
    • Software
    • Theoretical Computer Science

    Cite this

    Knowledge acquisition from time series data through rough sets analysis. / Matsumoto, Yoshiyuki; Watada, Junzo.

    In: International Journal of Innovative Computing, Information and Control, Vol. 5, No. 12, 12.2009, p. 4885-4897.

    Research output: Contribution to journalArticle

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