Semestral Project
Proposed topics cover the Networks Science area. Real data from various application domains can be represented as a graph (by a set of vertices connected by edges), or more precisely as a network. What the network and the networks science in general is you can find at http://barabasi.com/networksciencebook/ , https://en.wikipedia.org/wiki/Network_science , https://en.wikipedia.org/wiki/Complex_network , etc.
Possible topics:
1. The detection of communities in large networks using the weighted Max-Min modularity (on the basis of: Jiyang Chen, Osmar R. Zaïane, Randy Goebel: Detecting Communities in Social Networks Using Max-Min Modularity. SDM 2009: 978-989,
https://pdfs.semanticscholar.org/66e7/bf21fada27712cf9ca7ffe3591f074e85031.pdf )
2. Evolution of communities in temporal networks (on the basis of: Takaffoli, M., Fagnan, J., Sangi, F., Zaïane, O. R. (2011). Tracking changes in dynamic information networks. In Computational Aspects of Social Networks (CASoN), 2011 International Conference on (pp.
94-101). IEEE, http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6085925 )
3. Weighing in dynamic networks using forgetting functions (on the basis of: Milos Kudelka, Zdenek Horak, Václav Snásel, Pavel Krömer, Jan Platos, Ajith Abraham: Social and swarm aspects of co-authorship network. Logic Journal of the IGPL 20(3): 634-643 (2012), http://2.softcomputing.net/logic2011a.pdf )
4. Visualization of the temporal evolution network (on the basis of: Holme, P., Saramäki, J. (2012). Temporal networks. Physics reports, 519(3), 97-125, https://arxiv.org/pdf/1108.1780.pdf )
5. Generating network with community structure (on the basis of: Bianconi, G., Darst, R. K., Iacovacci, J., Fortunato, S. (2014). Triadic closure as a basic generating mechanism of
communities in complex networks. Physical Review E, 90(4), 042806, https://arxiv.org/pdf/1407.1664.pdf )
6. Analysis of egocentric network (on the basis of: Crossley, N., Bellotti, E., Edwards, G., Everett, M. G., Koskinen, J., Tranmer, M. (2015). Social network analysis for ego-nets: Social network analysis for actor-centred networks. SAGE)
The expected outputs of the project are:
• Source code in C# (Java, C++)
• The user interface for performing experiments
• Text (10-20 pages, including figures and tables)
• Presentation (about 10 minutes)
• Experimental data
Requirements for the source code:
• Object-oriented structure
• Configuring and managing the experiments according to the configuration file
• Commented source code
Structure of the text description:
• Introduction
• A survey of similar approaches (related works)
• Detailed description of the selected algorithms
• Design and settings of experiments
• Evaluation and interpretation of experimental results (supplemented by tables and figures)