Knowledge based Recommendation System in Semantic Web - A Survey

TLDR: Different techniques used to generate knowledge-based recommendations are explored highlighting the advantages of knowledge based recommendation system over other recommendation techniques.

Abstract: Knowledge based recommendation systems use knowledge about users and products to make recommendations. Knowledge-based recommendations are not dependent on the rating, nor do they have to gather information about a particular user to give recommendations. Knowledge acquisition is the most important task for constructing knowledge-based recommendation system. Acquired knowledge must be represented in some structured machine-readable form, e.g., as ontology to support reasoning about what products meets the user’s requirements. In Semantic Web, knowledge is represented in the form of ontology. Representation of knowledge in structured form of ontology in Semantic Web makes the application of knowledge based recommendations system on Semantic Web very easy, as there is no need to construct knowledge base from scratch. Performance of knowledge based recommendations systems can be enhanced by exploiting ontology reasoning characteristics. This paper explores different techniques used to generate knowledge-based recommendations highlighting the advantages of knowledge based recommendation system over other recommendation techniques.