A new insight into the linguistic summarization of time series via a degree of support: Elimination of infrequent patterns

Abstract

We extend our previous works on using a fuzzy logic based calculus of linguistically quantified propositions for linguistic summarization of time series (cf. Kacprzyk, Wilbik and Zadrozy [4, 5, 6, 7, 8, 9, 10, 11, 12, 13]. That approach, using the classic degree of truth (validity) to be maximized, is here extended by adding a degree of support. On the one hand, this can reflect in natural language the essence of traditional statistical approaches, and on the other hand, can help discard linguistic summaries with a high degree of truth but a low degree of support so that they concern infrequently occurring patterns and may be uninteresting. We show an application to the absolute performance analysis of an investment (mutual) fund. © 2008 Springer-Verlag Berlin Heidelberg.