Recommender Systems. Case iKnow: Composition of the required building blocks for the development of recommender systems

Abstract

In a period of time where knowledge management is a very important issue and the problem of information overload is growing, there is a need for systems that can help to obtain information, knowledge and data. The information and knowledge necessary for decision-making needs to be available and accessible in an easy way for the right person, at the time the information or knowledge is needed. This is where recommender systems come in.

Recommender systems are software systems that supply users with information in order to help them make decisions or to solve problems, without users have to search for it themselves.

A case study executed in cooperation with iKnow, in combination with a literature review, results in a description of a proposition for a recommender system.

The recommender system described in this paper is based on the Semantic Web and Linked Data. It uses the SPARQL query language to query RDF files.