Towards ranking in folksonomies for personalized recommender systems in e-learning
Mojisola Anjorin, Christoph Rensing, Ralf Steinmetz · 2011
Abstract. Recommender systems offer the opportunity for users to no longer have to search for resources but rather have these resources offered to them considering their personal needs and contexts. Additional semantics found in a folksonomy can be exploited to enhance the ranking of resources. These semantics have been analyzed in an e-learning scenario: CROKODIL. CROKODIL is a platform which supports the collaborative acquisition and management of learning resources. This paper proposes a conceptual architecture describing how these semantics can be integrated in a personalized recommender system for learning purposes. 1