Fuzzy Logic Applications for Knowledge Discovery: a Survey

Abstract

In this paper, we present a survey on Fuzzy Logic (FL) applications for Knowledge Discovery (KD), focusing on Information Retrieval (IR) and Information Extraction (IE). KD has been widely used for the search of information in vague, imprecise and noisy environments. Computational Intelligence, and mainly Fuzzy Logic, emerges as an ideal tool for IR and IE systems. We introduce a huge variety of FL applications, using the two main existing approaches: the applications based on the Vector Space Model (VSM); and the applications based on ontologies. For VSM applications, we split the applications into those related to queries, clustering, user profiles and hierarchical relations. Meanwhile, we also consider ontology applications, later focusing in the semantic web. However, all these applications are closely related.Section 3 introduces the state of the art of FL applications for IE and IR. It is divided in two sections, which correspond to the two main trends nowadays: VSM (Vector Space Model)-based applications and ontology-based applications.Section 4 shows the main conclusions of this survey.