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

Ram Keralapura, Antonio Nucci, Zhi Li Zhang, Lixin Gao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

63 Scopus citations

Abstract

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-clustering methodology, Phantom, using a novel hourglass model. The proposed hourglass model first reduces the dimensions of the input data and performs divisive hierarchical co-clustering on the lower dimensional data; it then carries out an expansion step that restores the original dimensions. Applying Phantom to the mobile network data, we find that there exists a number of prevalent and distinct behavior patterns that persist over time, suggesting that user browsing behavior in 3G cellular networks can be captured using a small number of co-clusters. For instance, behavior of most users can be classified as either homogeneous (users with very limited set of browsing interests) or heterogeneous (users with very diverse browsing interests), and such behavior profiles do not change significantly at either short (30-min) or long (6 hour) time scales.

Original languageEnglish (US)
Title of host publicationMobiCom'10 and MobiHoc'10 - Proceedings of the 16th Annual International Conference on Mobile Computing and Networking and 11th ACM International Symposium on Mobile Ad Hoc Networking and Computing
PublisherAssociation for Computing Machinery
Pages341-351
Number of pages11
ISBN (Print)9781450301817
DOIs
StatePublished - Jan 1 2010
Event16th Annual Conference on Mobile Computing and Networking, MobiCom 2010 - Chicago, IL, United States
Duration: Sep 20 2010Sep 24 2010

Publication series

NameProceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM

Conference

Conference16th Annual Conference on Mobile Computing and Networking, MobiCom 2010
CountryUnited States
CityChicago, IL
Period9/20/109/24/10

Keywords

  • Hierarchical co-clustering
  • Hourglass model
  • Phantom bi-clustering

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  • Cite this

    Keralapura, R., Nucci, A., Zhang, Z. L., & Gao, L. (2010). Profiling users in a 3G network using hourglass co-clustering. In MobiCom'10 and MobiHoc'10 - Proceedings of the 16th Annual International Conference on Mobile Computing and Networking and 11th ACM International Symposium on Mobile Ad Hoc Networking and Computing (pp. 341-351). (Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM). Association for Computing Machinery. https://doi.org/10.1145/1859995.1860034