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PNS: A Personalized News Aggregator on the Web

Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 104)

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.

Keywords

User Study News Item News Source Personalization Parameter Content Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  1. 1.Institute of Informatics and TelecommunicationsNational Center for Scientific Research “Demokritos”AthensGreece
  2. 2.Department of InformaticsTechnological Institute of AthensAthensGreece

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