Linguistic summarization of time series using a fuzzy quantifier driven aggregation.

Janusz Kacprzyk*, Anna Wilbik, Slawomir Zadrozny

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


We propose new types of linguistic summaries of time-series data that extend those proposed in our previous papers. The proposed summaries of time series refer to the summaries of trends identified here with straight line segments of a piecewise linear approximation of time series. We first show how to construct such an approximation. Then we employ a set of features (attributes) to characterize the trends such as the slope of the line segment, the goodness of approximation and the length of the trend. The derivation of a linguistic summary of a time series is then related to a linguistic quantifier driven aggregation of trends. For this purpose we employ the classic Zadeh's calculus of linguistically quantified propositions but, extending our previous works, with different t-norms in addition to the basic minimum. We show an application to the analysis of time-series data on daily quotations of an investment fund over an eight year period, present some interesting linguistic summaries obtained, and show results for different t-norms. The results are very promising. (C) 2008 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)1485-1499
JournalFuzzy Sets and Systems
Issue number12
Publication statusPublished - 2008
Externally publishedYes


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