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Title: Semantic Recommender Systems for Digital TV: From Demographic Stereotyping to Personalized Recommendations
Authors: Avila, J
Espinoza Mejía, Jorge Mauricio
Palacio Baus, Kenneth Samuel
Riofrio Machado, Xavier Fernando
Saquicela Galarza, Víctor Hugo
metadata.dc.ucuenca.nombrerevista: Asia-Pacific Conference on Computer-Aided System Engineering APCASE 2015
Keywords: Cold-Start
Demographic Stereotyping
Semantic Recommender System
Issue Date: 14-Jul-2015
metadata.dc.ucuenca.embargoend: 1-Jan-2022
metadata.dc.source: Proceedings - 2015 Asia-Pacific Conference on Computer-Aided System Engineering, APCASE 2015
metadata.dc.identifier.doi: 10.1109/APCASE.2015.76
metadata.dc.type: Article
Compared to analog transmissions, Digital Television (DTV) standards allows a higher number of available TV stations and consequently, a larger entertainment offer. In this context, Recommender Systems (RS) support users in choosing entertainment content by narrowing their options to a reduced set based on their preferences an interests. However, new users or those having incomplete profiles prevent the system to produce accurate recommendations, which is more noticeable in early stages of the RS. This paper proposes the use of a demographic stereotyping approach based on minimal user attributes acquired during user registration. Furthermore, we propose an experimental procedure that can be used to compare the system accuracy for the created stereotypes and for users making extensive use of the system.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959335625&doi=10.1109%2fAPCASE.2015.76&partnerID=40&md5=632aef13d8faefefcaa0b2ac5ded1bf7
ISBN: 9781479975884
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