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Article
Inferring Future Links in Large Scale Networks
Proceedings of the IEEE 41st Conference on Local Computer Networks (2016, Dubai, United Arab Emirates)
  • Sima Das
  • Sajal K. Das, Missouri University of Science and Technology
  • Susmita Ghosh
Abstract

The challenge in predicting future links over large scale networks (social networks) is not only maintaining accuracy, but also coping with the time-varying network graph. In contrast to the existing approaches, in this work we propose building a Markov prediction model. It not only incorporates temporal snapshots reflecting the dynamic network graph, but also considers effect of multiple timescales, along with corresponding local and global structural evolution (links and clusters respectively), correlated evolution and rate of evolution. The resulting edge selection in our approach exhibits the power law degree distribution, as exhibited in real world networks. Finally, we use two heavily dynamic real world network temporal data set (e.g. Twitter and Enron) and one relatively less dynamic network data set (e.g. DBLP), and existing state-of-the-art static and recent dynamic measures, to evaluate the prediction accuracy of our proposed Markov model and show that it out performs existing approaches.

Meeting Name
IEEE 41st Conference on Local Computer Networks, LCN 2016 (2016: Nov. 7-10, Dubai, United Arab Emirates)
Department(s)
Computer Science
Research Center/Lab(s)
Intelligent Systems Center
Comments
This work is partially supported by NSF grants under award numbers CCF-1533918 and CNS-1355505.
Keywords and Phrases
  • Forecasting,
  • Markov processes,
  • Dynamic measures,
  • Large-scale network,
  • Multiple timescales,
  • Power law degree distribution,
  • Prediction accuracy,
  • Real-world networks,
  • State of the art,
  • Structural evolution,
  • Computer networks
International Standard Book Number (ISBN)
978-1-5090-2054-6
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2016 Sima Das. Under license to IEEE., All rights reserved.
Publication Date
11-1-2016
Disciplines
Citation Information
Sima Das, Sajal K. Das and Susmita Ghosh. "Inferring Future Links in Large Scale Networks" Proceedings of the IEEE 41st Conference on Local Computer Networks (2016, Dubai, United Arab Emirates) (2016) p. 244 - 252
Available at: http://works.bepress.com/sajal-das/75/