Handling shape variations in geographical distance rankings for local news recommendation

Geographical proximity is an important ranking feature in many context aware recommendation systems. News recommender systems are an example of such systems where the proximity between users and the news' geographical context is a particularly important relevance factor. In this paper, we will discuss ways to improve distance ranking by taking geographical entity sizes, shapes, and footprints into account when handling news items that are ranked for specific users.