Skip to main content
Article thumbnail
Location of Repository

A REGULARIZATION FRAMEWORK FOR MOBILE SOCIAL NETWORK ANALYSIS

By Xiaowen Dong, Pascal Frossard, Pierre V and Nikolai Nefedov

Abstract

Mobile phone data provides rich dynamic information on human activities in social network analysis. In this paper, we represent data from two different modalities as a graph and functions defined on the vertex set of the graph. We propose a regularization framework for the joint utilization of these two modalities of data, which enables us to model evolution of social network information and efficiently classify relationships among mobile phone users. Simulations based on real world data demonstrate the potential application of our model in dynamic scenarios, and present competitive results to baseline methods for combining multimodal data in the learning and clustering communities. Index Terms — Multimodal data, regularization on graphs, classification and clusterin

Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.190.6603
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://infoscience.epfl.ch/rec... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.