@inproceedings{5b5f1981a4614e10aa14ac47b59a9b02,
title = "Improving Cold-Start Recommendations with Social-Media Trends and Reputations",
abstract = "In recommender systems, the cold-start problem is a common challenge. When a new item has no ratings, it becomes difficult to relate it to other items or users. In this paper, we address the cold-start problem and propose to leverage on social-media trends and reputations to improve the recommendation of new items. The proposed framework models the long-term reputation of actors and directors, to better characterize new movies. In addition, movies popularity are deduced from social-media trends that are related to the corresponding new movie. A principled method is then applied to infer cold-start recommendations from these social-media signals. Experiments on a realistic time-frame, covering several movie-awards events between January 2014 and March 2014, showed significant improvements over ratings-only and metadata-only based recommendations.",
keywords = "Cold-start, Online reputation, Recommendation, Sentiment analysis, Social-media",
author = "Jo{\~a}o Santos and Filipa Peleja and Fl{\'a}vio Martins and Jo{\~a}o Magalh{\~a}es",
note = "info:eu-repo/grantAgreement/EC/H2020/687605/EU# info:eu-repo/grantAgreement/FCT/5876/147279/PT# CMU Portugal research project GoLocal Ref. CMUP-ERI/TIC/0033/2014. ; 16th International Symposium on Intelligent Data Analysis, IDA 2017 ; Conference date: 26-10-2017 Through 28-10-2017",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-68765-0_25",
language = "English",
isbn = "978-3-319-68764-3",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "297--309",
editor = "Niall Adams and Allan Tucker and David Weston",
booktitle = "Advances in Intelligent Data Analysis XVI - 16th International Symposium, IDA 2017, Proceedings",
address = "Germany",
}