Data-driven co-clustering model of internet usage in large mobile societies

  • Authors:
  • Saeed Moghaddam;Ahmed Helmy;Sanjay Ranka;Manas Somaiya

  • Affiliations:
  • University of Florida, Gainesville, FL, USA;University of Florida, Gainesville, FL, USA;University of Florida, Gainesville, FL, USA;University of Florida, Gainesville, FL, USA

  • Venue:
  • Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

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 co-clustering 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.