DynamicTV: a culture-aware recommender

Authors:
Fabrizio Antonelli;Gianluca Francini;Marina Geymonat;Skjalg Lepsøy
Affiliations:
Telecom Italia Lab, Torino, Italy;Telecom Italia Lab, Torino, Italy;Telecom Italia Lab, Torino, Italy;Telecom Italia Lab, Torino, Italy
Venue:
Proceedings of the third ACM conference on Recommender systems
Year:
2009

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Abstract

A geographically homogeneous group of citizens shares much common knowledge, characteristics of their culture and history. This knowledge is captured for the use in an item-based recommender system that uses textual information, by introducing bias corpora: newspaper articles that represent the shared knowledge. We present a technique for incorporating and quickly replacing bias corpora in a case study of recommendation of TV contents on our IPTV platform. With this recommender, users watched more items and expressed satisfaction with the service.