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.
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Cleger-Tamayo, S., Fernández-Luna, J.M., Huete, J.F., Pérez-Vázquez, R., Rodríguez Cano, J.C. (2010). A Proposal for News Recommendation Based on Clustering Techniques. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6098. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13033-5_49
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DOI: https://doi.org/10.1007/978-3-642-13033-5_49
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