Comprehensiveness and interpretability of linguistic data summaries: A natural language focused perspective
We extend our previous works of deriving linguistic summaries of time series using a fuzzy logic approach. To obtain a more advanced evaluation of summaries, we perform a multi-criteria analysis of summaries by assuming as a unifying quality criterion Yager’s measure of informativeness of the classic and temporal protoforms that combines in a natural way the measures of truth, focus and specificity. The use of the measure of informativeness for this purpose seems to be an effective and efficient approach, yet simple enough for practical applications. Results on the summarisation of quotations of an investment (mutual) fund are very encouraging.