A proposal for news recommendation based on clustering techniques

Authors:
Sergio Cleger-Tamayo;Juan M. Fernández-Luna;Juan F. Huete;Ramiro Pérez-Vázquez;Julio C. Rodríguez Cano
Affiliations:
Department of Informatics. University of Holguín, Cuba;Departamento de Ciencias de la Computación e Inteligencia Artificial, CITIC, E.T.S.I Informática y de Telecomunicación, Universidad de Granada, Granada, Spain;Departamento de Ciencias de la Computación e Inteligencia Artificial, CITIC, E.T.S.I Informática y de Telecomunicación, Universidad de Granada, Granada, Spain;Departament of Computer Science. University Central de las Villas, Cuba;Department of Informatics. University of Holguín, Cuba
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Year:
2010

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Abstract

The application of clustering techniques in recommendation systems is discussed in the present article, specifically in a journalistic context, where multiple users have access to categorized news. The aim of this paper is to present an approach to recommend news to the readers of an electronic journal according to their profile, i.e. the record of news accessed. The Aspect Model, as well as the K-Means clustering algorithm are applied to this problem and compared empirically.