Abstract
We consider an extension to a new approach to the linguistic summarization of time series data proposed in our previous papers. We summarize trends identified here with straight segments of a piecewise linear approximation of time series. Then we employ, as a set of features, the duration, dynamics of change and variability, and assume different, human consistent granulations of their values. The problem boils down to a linguistic quantifier driven aggregation of partial trends that is done via the classic Zadeh’s calculus of linguistically quantified propositions but with different t-norms. We show an application to linguistic summarization of time series data on daily quotations of an investment fund over an eight year period.
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Kacprzyk, J., Wilbik, A., Zadrożny, S. (2007). Linguistic Summarization of Time Series Under Different Granulation of Describing Features. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds) Rough Sets and Intelligent Systems Paradigms. RSEISP 2007. Lecture Notes in Computer Science(), vol 4585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73451-2_25
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DOI: https://doi.org/10.1007/978-3-540-73451-2_25
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