Knowledge acquisition from time series data through rough sets analysis

Yoshiyuki Matsumoto; Junzo Watada

Knowledge acquisition from time series data through rough sets analysis

Yoshiyuki Matsumoto^*, Junzo Watada

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	4885-4897
Number of pages	13
Journal	International Journal of Innovative Computing, Information and Control
Volume	5
Issue number	12
Publication status	Published - 2009 Dec

Keywords

Knowledge acquisition
Rought sets
Time series data

ASJC Scopus subject areas

Computational Theory and Mathematics
Information Systems
Software
Theoretical Computer Science

Cite this

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Knowledge acquisition from time series data through rough sets analysis

Abstract

Keywords

ASJC Scopus subject areas

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