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A User-Centered Approach for Social Recommendations

Authors:
Francesco Colace
Massimo De Santo
Luca Greco
Flora Amato
Vincenzo Moscato
Fabio Persia
Antonio Picariello

Keywords: Recommender Systems; Sentiment Analysis; Context- Awareness

Abstract:
Recommender Systems represent useful tools helping users to find “what they need” from a very large number of candidates and supporting people in making decisions in several contexts. In this paper, we propose a novel user-centered and social recommendation approach in which several aspects related to users, i.e., preferences, opinions, behavior, feedbacks, are considered and integrated together with items’ features and context information within a general framework that can support different applications using proper customizations (e.g., recommendation of news, photos, movies, travels, etc.). Preliminary experiments on system accuracy show how our approach provides very promising and interesting results.

Pages: 190 to 193

Copyright: Copyright (c) IARIA, 2015

Publication date: February 22, 2015

Published in: conference

ISSN: 2308-4138

ISBN: 978-1-61208-382-7

Location: Lisbon, Portugal

Dates: from February 22, 2015 to February 27, 2015