Recent literature predicts that including context in a recommender system may improve its performance. The context-based recommendation approaches are classified as pre-filtering, post-filtering and contextual modeling. Little research has been done on studying whether including context in a recommender system improves the recommendation performance and no research has compared yet the different approaches to contextual RS. The research contribution of this work lies in studying the effect of the context on the recommendation performance and comparing a pre-filtering approach to a post-filtering using a collaborative filtering recommender system.
|Titolo:||Comparing Pre-filtering and Post-filtering Approach in a Collaborative Contextual Recommender System: An Application to E-Commerce|
|Data di pubblicazione:||2009|
|Nome del convegno:||10th International Conference, EC-Web 2009|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1007/978-3-642-03964-5_32|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|