  Design and simulation of future mobile networks will center around human
interests and behavior. We propose a design paradigm for mobile networks driven
by realistic models of users' on-line behavior, based on mining of billions of
wireless-LAN records. We introduce a systematic method for large-scale
multi-dimensional coclustering of web activity for thousands of mobile users at
79 locations. We find surprisingly that users can be consistently modeled using
ten clusters with disjoint profiles. Access patterns from multiple locations
show differential user behavior. This is the first study to obtain such
detailed results for mobile Internet usage.
