This paper presents a system that aggregates news from various electronic news publishers and distributors. The system collects news from HTML and RSS Web documents by using source-specific information extraction programs (wrappers) and parsers, organizes them according to pre-defined news categories and constructs personalized views via a Web-based interface. Adaptive personalization is performed, based on the individual user interaction, user similarities and statistical analysis of aggregate usage data by machine learning algorithms. In addition to the presentation of the basic system, we present here the results of a user study, indicating the merits of the system, as well as ways to improve it further.
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Paliouras, G., Mouzakidis, A., Moustakas, V., Skourlas, C. (2008). PNS: A Personalized News Aggregator on the Web. In: Virvou, M., Jain, L.C. (eds) Intelligent Interactive Systems in Knowledge-Based Environments. Studies in Computational Intelligence, vol 104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77471-6_10
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DOI: https://doi.org/10.1007/978-3-540-77471-6_10
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