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

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