News recommendation in Indonesian language based on user click behavior
Diandra Mayang Desyaputri, Alva Erwin, Maulahikmah Galinium, Didi Nugrahadi · 2013
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.