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

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.