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Title: Decategorizing demographically stereotyped users in a semantic recommender system
Authors: Avila, J
Astudillo Salinas, Darwin Fabián
Espinoza Mejía, Jorge Mauricio
Palacio Baus, Kenneth Samuel
Riofrio Machado, Xavier Fernando
Saquicela Galarza, Víctor Hugo
metadata.dc.ucuenca.nombrerevista: 42nd Latin American Computing Conference CLEI 2016
Issue Date: 10-Oct-2016
metadata.dc.ucuenca.embargoend: 1-Jan-2022
metadata.dc.source: Proceedings of the 2016 42nd Latin American Computing Conference, CLEI 2016
metadata.dc.identifier.doi: 10.1109/CLEI.2016.7833408
metadata.dc.type: Article
In the domain of Digital Television (DTV) broadcasting technology, the enhancement of signals features over classic analog signal transmission allows increasing the amount of content available for TV viewers. Recommender Systems (RS) arose as a suitable choice to assist users in the overwhelming task of selecting audiovisual content, however, the cold-start problem normally associated to the lack of information in early RS stages, causes that user stereotyping approaches are employed meanwhile the lack of information in user profiles is overcome. This paper presents an experimental approach aimed to determine the best conditions for which users who were categorized within a determined stereotype during the cold-start stage, could migrate to a new state in which they receive personalized recommendations. Experimental results show that the best condition under the selected demographic stereotyping scheme for this transition is directly related to the number of TV programs that a user has rated while making use of the system.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013897404&doi=10.1109%2fCLEI.2016.7833408&partnerID=40&md5=7b43473d3ccbd69828a7935f63d8efe0
ISBN: 9781509016334
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