CROWN: A Context-aware RecOmmender for Web News

It is popular for most people to read news online since the web sites can provide access to news articles from millions of sources around the world. For these news web sites, the key challenge is to help users find related news articles to read. In this paper, we present a system called CROWN (Context-aware RecOmmender for Web News) to do Chinese news recommendation. By recommendation, the system can retrieve personalized fresh and relevant news articles to mobile users according to their particular context. Differing from existing mobile news applications which employ rather simple strategies for news recommendation, CROWN integrates the contextual information in prediction by modeling the data as a tensor. Such context information usually includes the time, the location, etc. This demo paper presents the implementation of the whole procedure of news recommendation in the system of CROWN. Experimental results on a large corpus of newly-published Chinese web news show its performance is satisfactory.