A Multi-criteria Evaluation of Linguistic Summaries of Time Series via a Measure of Informativeness

Anna Wilbik; Janusz Kacprzyk

doi:10.1007/978-3-642-13208-7_14

A Multi-criteria Evaluation of Linguistic Summaries of Time Series via a Measure of Informativeness

Anna Wilbik
, Janusz Kacprzyk

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

We extend our works of deriving linguistic summaries of time series using a fuzzy logic approach to linguistic summarization. We proceed towards a multicriteria analysis of summaries by assuming as a quality criterion yager’s measure of informativeness that combines in a natural way the measures of truth, focus and specificity, to obtain a more advanced evaluation of summaries. The use of the informativeness measure for the purpose of a multicriteria evaluation of linguistic summaries of time series seems to be an effective and efficient approach, yet simple enough for practical applications. Results on the summarization of quotations of an investment (mutual) fund are very encouraging.

Original language	English
Title of host publication	Artificial Intelligence and Soft Computing
Chapter	14
Pages	105-113
ISBN (Electronic)	9783642132087
DOIs	https://doi.org/10.1007/978-3-642-13208-7_14
Publication status	Published - 2010
Externally published	Yes

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abstract = "We extend our works of deriving linguistic summaries of time series using a fuzzy logic approach to linguistic summarization. We proceed towards a multicriteria analysis of summaries by assuming as a quality criterion yager{\textquoteright}s measure of informativeness that combines in a natural way the measures of truth, focus and specificity, to obtain a more advanced evaluation of summaries. The use of the informativeness measure for the purpose of a multicriteria evaluation of linguistic summaries of time series seems to be an effective and efficient approach, yet simple enough for practical applications. Results on the summarization of quotations of an investment (mutual) fund are very encouraging.",

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AU - Kacprzyk, Janusz

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N2 - We extend our works of deriving linguistic summaries of time series using a fuzzy logic approach to linguistic summarization. We proceed towards a multicriteria analysis of summaries by assuming as a quality criterion yager’s measure of informativeness that combines in a natural way the measures of truth, focus and specificity, to obtain a more advanced evaluation of summaries. The use of the informativeness measure for the purpose of a multicriteria evaluation of linguistic summaries of time series seems to be an effective and efficient approach, yet simple enough for practical applications. Results on the summarization of quotations of an investment (mutual) fund are very encouraging.

AB - We extend our works of deriving linguistic summaries of time series using a fuzzy logic approach to linguistic summarization. We proceed towards a multicriteria analysis of summaries by assuming as a quality criterion yager’s measure of informativeness that combines in a natural way the measures of truth, focus and specificity, to obtain a more advanced evaluation of summaries. The use of the informativeness measure for the purpose of a multicriteria evaluation of linguistic summaries of time series seems to be an effective and efficient approach, yet simple enough for practical applications. Results on the summarization of quotations of an investment (mutual) fund are very encouraging.

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EP - 113

BT - Artificial Intelligence and Soft Computing

ER -

A Multi-criteria Evaluation of Linguistic Summaries of Time Series via a Measure of Informativeness

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