student profile: Mr Nazim Choudhury


Map

Thesis work

Thesis title: Time Aware Link Prediction and Community Detection in Longitudinal Network

Supervisors: Shahadat UDDIN , Ken CHUNG

Thesis abstract:

Longitudinal networks evolve through simultaneous arrivals and/or departure of actors as well as creation and/or deletion of links among these actors. Increased availability of real-world longitudinal network datasets has prompted longitudinal network analysis to gain considerable research interests to better understand the underlying mechanisms of its evolutionary dynamics. In relation to evolutionary network analysis, different link prediction and community detection methods in network science support not only the prediction of future links and modelling of their dynamics but also help in detecting the actors' inclination towards clustering . The most potential limitation of these link prediction methods is their static nature of observation and failure to taking into account the network evolution.Longitudinal networks cater information of more than one network states that can be beneficial to understand the future link formation. Therefore, it is worthwhile to consider the temporal information of structural changes occurs in longitudinal networks in order to measure the possibility of the future link and community formation. The similarity between temporal sequences of structural and dynamic changes associated with individual actors can be utilised to predict future links and detect community in longitudinal networks. In this research, I aim to analyze time series of simple network structural information (i.e., different centrality measures, connectivity) and different types actor dynamicities (i.e., positional and participation) of non-connected node pairs that changes over time in longitudinal network to successfully predict future links among them and detect the community structure that take place in longitudinal network.

Selected publications

Download citations: PDF RTF Endnote

Journals

  • Khan, M., Choudhury, N., Uddin, M., Hossain, L., Baur, L. (2016). Longitudinal trends in global obesity research and collaboration: a review using bibliometric metadata. Obesity Reviews, 17(4), 377-385. [More Information]
  • Choudhury, N., Uddin, M. (2016). Time-aware link prediction to explore network effects on temporal knowledge evolution. Scientometrics, 108(2), 745-776. [More Information]

Conferences

  • Choudhury, N., Uddin, M. (2017). Evolution Similarity for Dynamic Link Prediction in Longitudinal Networks. 8th International Conference on Complex Networks (CompleNet) 2017, Switzerland: Springer International Publishing. [More Information]

2017

  • Choudhury, N., Uddin, M. (2017). Evolution Similarity for Dynamic Link Prediction in Longitudinal Networks. 8th International Conference on Complex Networks (CompleNet) 2017, Switzerland: Springer International Publishing. [More Information]

2016

  • Khan, M., Choudhury, N., Uddin, M., Hossain, L., Baur, L. (2016). Longitudinal trends in global obesity research and collaboration: a review using bibliometric metadata. Obesity Reviews, 17(4), 377-385. [More Information]
  • Choudhury, N., Uddin, M. (2016). Time-aware link prediction to explore network effects on temporal knowledge evolution. Scientometrics, 108(2), 745-776. [More Information]

Note: This profile is for a student at the University of Sydney. Views presented here are not necessarily those of the University.