NectaRSS, an intelligent RSS feed reader

In this paper a novel article ranking method called NectaRSS is introduced. The system recommends incoming articles, which we will designate as newsitems, to users based on their past choices. User preferences are automatically acquired, avoiding explicit feedback, and ranking is based on those pref...

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Bibliographic Details
Published in:Journal of network and computer applications 2008-11, Vol.31 (4), p.793-806
Main Authors: Samper, Juan J., Castillo, Pedro A., Araujo, Lourdes, Merelo, J.J., Cordón, Óscar, Tricas, Fernando
Format: Article
Language:English
Subjects:
Applied sciences
Exact sciences and technology
Information retrieval
Information theory
Information, signal and communications theory
RSS
Telecommunications and information theory
User profiling
Weblogs
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Summary:In this paper a novel article ranking method called NectaRSS is introduced. The system recommends incoming articles, which we will designate as newsitems, to users based on their past choices. User preferences are automatically acquired, avoiding explicit feedback, and ranking is based on those preferences distilled to a user profile. NectaRSS uses the well-known vector space model for user profiles and new documents, and compares them using information retrieval techniques, but introduces a novel method for user profile creation and adaptation from users’ past choices. The efficiency of the proposed method has been tested by embedding it into an intelligent aggregator (RSS feed reader) which has been used by different and heterogeneous users. Besides, this paper proves that the ranking of newsitems yielded by NectaRSS improves its quality with user's choices, and its superiority over other algorithms that use a different information representation method.
ISSN:1084-8045
1095-8592
DOI:10.1016/j.jnca.2007.09.001