Modal linguistic summaries based on natural language equivalence with cognitive semantics

Abstract

An original model of linguistic summaries extracted from episodic data is briefly presented. In particular, a class of linguistic summaries expressed as modal equivalences is considered. The model is tailored to the concept of autonomous agent systems, and is supported by several detailed, non-technical, natural language processing and knowledge representation theories. Complementary to the well known classic interpretation of linguistic summaries, based on the fuzzy sets theory, the proposed model deals with a different class of vague cognitive concepts. The class consists of epistemic modalities, in particular the concepts of knowledge, belief and possibility. Each sub-class of linguistic summaries is processed as understood in the context of natural systems and supported by related cognitive semantics. Remarks on relevant implementation technologies are given, and an illustrative computational example is presented.