Linguistic summaries of time series via a quantifier based aggregation using the Sugeno integral

J. Kacprzyk; A. Wilbik; S. Zadrozny

doi:10.1109/FUZZY.2006.1681789

Linguistic summaries of time series via a quantifier based aggregation using the Sugeno integral

J. Kacprzyk^*, A. Wilbik, S. Zadrozny

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

Linguistic summaries as descriptions of trends in time series data are proposed. Two general types of such summaries are discussed. The point of departure are linguistic summaries of databases due to Yager. The specificity of time series summarization requires a more general approach to linguistic quantifier based aggregation. Sugeno integrals are employed to address this problem.

Original language	English
Title of host publication	Proceedings of 2006 IEEE World Congress on Computational Intelligence
Publisher	IEEE Press
Pages	713-719
Number of pages	7
DOIs	https://doi.org/10.1109/FUZZY.2006.1681789
Publication status	Published - 2006
Externally published	Yes

Access to Document

10.1109/FUZZY.2006.1681789

Cite this

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title = "Linguistic summaries of time series via a quantifier based aggregation using the Sugeno integral",

abstract = "Linguistic summaries as descriptions of trends in time series data are proposed. Two general types of such summaries are discussed. The point of departure are linguistic summaries of databases due to Yager. The specificity of time series summarization requires a more general approach to linguistic quantifier based aggregation. Sugeno integrals are employed to address this problem.",

author = "J. Kacprzyk and A. Wilbik and S. Zadrozny",

note = "2006 IEEE World Congress on Computational Intelligence (WCCI), 16-21 July 2006, Vancouver, Canada, WCCI2006 ; Conference date: 16-07-2006 Through 21-07-2006",

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AU - Wilbik, A.

AU - Zadrozny, S.

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AB - Linguistic summaries as descriptions of trends in time series data are proposed. Two general types of such summaries are discussed. The point of departure are linguistic summaries of databases due to Yager. The specificity of time series summarization requires a more general approach to linguistic quantifier based aggregation. Sugeno integrals are employed to address this problem.

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DO - 10.1109/FUZZY.2006.1681789

M3 - Conference article in proceeding

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BT - Proceedings of 2006 IEEE World Congress on Computational Intelligence

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