Recommending Social Events from Mobile Phone Location Data

A city offers thousands of social events a day, and it is difficult for dwellers to make choices. The combination of mobile phones and recommender systems can change the way one deals with such abundance. Mobile phones with positioning technology are now widely available, making it easy for people to broadcast their whereabouts; recommender systems can now identify patterns in people's movements in order to, for example, recommend events. To do so, the system relies on having mobile users who share their attendance at a large number of social events: cold-start users, who have no location history, cannot receive recommendations. We set out to address the mobile cold-start problem by answering the following research question: how can social events be recommended to a cold-start user based only on his home location? To answer this question, we carry out a study of the relationship between preferences for social events and geography, the first of its kind in a large metropolitan area...

• Type: Journal
• Year: 2010
• Where: ICDM
• Authors: Daniele Quercia, Neal Lathia, Francesco Calabrese, Giusy Di Lorenzo, Jon Crowcroft
• Keywords: Data Mining, ICDM 2010, Mobile Phone, Recommender Systems, Social Events