Paper Title :Keyword Based User Profiling for News Recommendation
Author :Aadhithya Sankar, Ela Nilavazhagan
Article Citation :Aadhithya Sankar ,Ela Nilavazhagan ,
(2016 ) " Keyword Based User Profiling for News Recommendation " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 64-67,
Volume-4, Issue-12
Abstract : News Recommendation is increasingly being deployed by online news publishers. Recommender Systems are
used as a way to deal with information overload and to increase page views. Collaborative filtering and content based
filtering are two common approaches used in recommendation systems. In this paper, we propose a News Recommendation
System Model that uses keywords obtained from the articles to profile the user. We then use a collaborative filtering model
to generate recommendations to the users. Coping with ever changing user interests is also a major challenge for
recommendation system. This model also proposes a decay function to deal with such a challenge.
Index Terms— Recommender Systems, Time Based, Keywords, Collaborative Filtering, Matrix Factorization
Type : Research paper
Published : Volume-4, Issue-12
DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-6462
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Copyright: © Institute of Research and Journals
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Published on 2017-01-17 |
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