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Title: PersoNews: A Personalized News Reader Enhanced by Machine Learning and Semantic Filtering
Author(s): E. Banos, I. Katakis, N. Bassiliades, G. Tsoumakas, I. Vlahavas.
Availability: Click here to download the PDF (Acrobat Reader) file (8 pages).
Keywords: News Filtering News Classification, Text Mining, Text Classification, Personalization, Ontology, RSS Aggregator, ..
Appeared in: 5th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2006), R. Meersman, Z. Tari (Ed.), Springer-Verlag, pp. 975-982, Montpellier, France, 2006.
Abstract: In this paper, we present a web-based, machine-learning enhanced news reader (PersoNews). The main advantages of PersoNews are the aggregation of many different news sources, machine learning filtering offering personalization not only per user but also for every feed a user is subscribed to, and finally the ability for every user to watch a more abstracted topic of interest by employing a simple form of semantic filtering through a taxonomy of topics. (URL: http://news.csd.auth.gr).
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