Title :
Reperio: A Generic and Flexible Industrial Recommender System
Author :
Meyer, Franck ; Fessant, Françoise
Author_Institution :
Orange Labs., Lannion, France
Abstract :
We describe Reperio, a flexible and generic industrial recommender system able to deal with several kinds of data sources (content-based, collaborative, social network...) into the same framework and to work on multi platforms (web service in a multi-users mode and mobile device in a mono-user mode). We present the architecture of the system and the main issues involved in its development.
Keywords :
data analysis; recommender systems; data source; flexible industrial recommender system; generic industrial recommender system; Catalogs; Collaboration; Computer architecture; Databases; Engines; Recommender systems; collaborative filtering; content-based filtering; embedded recommender system; recommender system design;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
Conference_Location :
Lyon
Print_ISBN :
978-1-4577-1373-6
Electronic_ISBN :
978-0-7695-4513-4
DOI :
10.1109/WI-IAT.2011.78
