Knowledge acquisition from time series data through rough sets analysis

Yoshiyuki Matsumoto*, Junzo Watada

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    27 Citations (Scopus)


    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
    Issue number12
    Publication statusPublished - 2009 Dec


    • Knowledge acquisition
    • Rought sets
    • Time series data

    ASJC Scopus subject areas

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


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