Title :
News recommendation in Indonesian language based on user click behavior
Author :
Desyaputri, Diandra Mayang ; Erwin, Alva ; Galinium, Maulahikmah ; Nugrahadi, Didi
Author_Institution :
Dept. of Inf. Technol., Swiss German Univ., Tangerang, Indonesia
Abstract :
Recommendation system has been proposed for years as the solution of information era problem. This research strives to develop an intelligent recommendation system based on user click behavior on news websites. We extracted frequent itemsets and association rules from the web server log of a news website, performed a pre-computation of similarity between news articles, and then proposed a three-level recommendation system: based on association rule discovery, news articles on the same category, and similarity between news articles. By combining collaborative filtering approach and content-based filtering, experiment results show that the technique produces reliable news recommendation.
Keywords :
collaborative filtering; data mining; recommender systems; Indonesian language; association rule discovery; association rules extraction; collaborative filtering approach; content-based filtering; frequent itemsets extraction; information era problem; intelligent recommendation system; news recommendation system; three-level recommendation system; user click behavior; association rules; news recommendation; similarity; web usage mining;
Conference_Titel :
Information Technology and Electrical Engineering (ICITEE), 2013 International Conference on
Conference_Location :
Yogyakarta
Print_ISBN :
978-1-4799-0423-5
DOI :
10.1109/ICITEED.2013.6676232
