Linguistic summarization of time series under different granulation of describing features

J. Kacprzyk, A. Wilbik, S. Zadrozny

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

28 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationRough Sets and Intelligent Systems Paradigms
Subtitle of host publicationInternational Conference, RSEISP 2007, Warsaw, Poland, June 28-30, 2007. Proceedings
EditorsM. Kryszkiewicz, J.F. Peters, H. Rybinski, A. Skowron
Place of PublicationBerlin
Number of pages11
ISBN (Electronic)978-3-540-73451-2
ISBN (Print)978-3-540-73450-5
Publication statusPublished - 2007
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (LNCS)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameLecture Notes in Artificial Intelligence (LNAI)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


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