Home // IMMM 2013, The Third International Conference on Advances in Information Mining and Management // View article
Authors:
Ludovico Boratto
Salvatore Carta
Keywords: Group Recommendation; Clustering; Ratings Prediction.
Abstract:
Recommender systems produce content for users, by suggesting items that users might like. Predicting the ratings is a key task in a recommender system. This is especially true in a system that works with groups, because ratings might be predicted for each user or for the groups. The approach chosen to predict the ratings changes the architecture of the system and what information is used to build the predictions. This paper studies approaches to predict the ratings in a group recommendation scenario that automatically detects groups. Experimental results confirm that the approach to predict the ratings strongly influences the performances of a system and show that building predictions for each user, with respect to building predictions for a group, leads to great improvements in the quality of the recommendations.
Pages: 36 to 43
Copyright: Copyright (c) IARIA, 2013
Publication date: November 17, 2013
Published in: conference
ISSN: 2326-9332
ISBN: 978-1-61208-311-7
Location: Lisbon, Portugal
Dates: from November 17, 2013 to November 21, 2013