Profiling users in a 3g network using hourglass co-clustering

With widespread popularity of smart phones, more and more users are accessing the Internet on the go. Understanding mobile user browsing behavior is of great significance for several reasons. For example, it can help cellular (data) service providers (CSPs) to improve service performance, thus increasing user satisfaction. It can also provide valuable insights about how to enhance mobile user experience by providing dynamic content personalization and recommendation, or location-aware services. In this paper, we try to understand mobile user browsing behavior by investigating whether there exists distinct "behavior patterns" among mobile users. Our study is based on real mobile network data collected from a large 3G CSP in North America. We formulate this user behavior profiling problem as a co-clustering problem, i.e., we group both users (who share similar browsing behavior), and browsing profiles (of like-minded users) simultaneously. We propose and develop a scalable co-...

• Type: Conference
• Year: 2010
• Where: MOBICOM
• Authors: Ram Keralapura, Antonio Nucci, Zhi-Li Zhang, Lixin Gao
• Keywords: Behavior, Communications, MOBICOM 2010, Mobile Network Data, Mobile Users