Efficient Product Choice through Ontology-based Recommender Systems
Nikolaos Tilipakis, Christos Douligeris · 2007
In this paper, we examine the issue of customer satisfaction through efficient recommender systems that are based on the semantic web. First, we present an overview of the field of recommender systems, describe the current generation of recommendation methods that are usually classified into two main categories, namely: content-based and collaborative recommendation approaches, and we point out various limitations of current recommendation methods. We then present the basic elements of a prototype recommender system for customer relations management that is based on ontologies and show how the semantic web can provide the underlying engine of recommender systems that are considerably better than previously proposed systems.