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Last update: RNDr. Ondřej Pangrác, Ph.D. (07.06.2021)
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Last update: RNDr. Ondřej Pangrác, Ph.D. (07.06.2021)
The course is organized in lectures providing basic theory on topics given above. Seminars deal with theoretical as well as practical problems of complex networks.
Continuous evaluation is based on a particular combination of test and individual work based on theoretical or practical problems. This may even include particular project aiming towards potential (diploma) thesis. Final evaluation consists of combined an oral exam. |
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Last update: RNDr. Ondřej Pangrác, Ph.D. (07.06.2021)
Basic literature Barabási, A.-L. Network science. Cambridge university press, 2016. Newman, MEJ Networks: An Introduction. Oxford University press, 2010. Latora, V., Nicosia, V, Russo, G. Complex networks, Cambridge University Press, 2017.
Extended literature Nešetřil, K., Ossona de Mendez. P. Sparsity: Graphs, Structures, and Algorithms. Springer, 2012. Frieze, A., Karoñski, M. Introduction to Random Graphs. Cambridge University Press, 2015. Godsil, C., Royle, G.F. Algebraic graph theory. Springer-Verlag, 2001. Brouwer, A.E., Haemers, W. H. Spectra of Graphs. Springer, 2012. Bollobas, B, Kozma, R., Miklós, D. Handbook of Large-Scale Random Networks, Springer, 2010. Lovász, L. Large Networks and Graph Limits. American Mathematical Society colloquium publications. American Mathematical Society, 2012. |
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Last update: RNDr. Ondřej Pangrác, Ph.D. (07.06.2021)
Teaching can take both personal as well as distance forms. Further information is available on the teachers' website:
https://iuuk.mff.cuni.cz/~hartman/teach/complex-network-analysis/ |
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Last update: RNDr. Ondřej Pangrác, Ph.D. (07.06.2021)
The requirements for the exam correspond to the syllabus of the course to the extent that it was covered in lectures, exercises and self-study. It is required as well as the ability to apply the acquired knowledge in solving examples or corresponding tasks.
The exam has just an oral form.
The exam can be in contact or distance form. |
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Last update: RNDr. Ondřej Pangrác, Ph.D. (07.06.2021)
1) Introduction to complex networks and recap of basic properties
small-world, community structure, etc. 2) Overview of basic properties
3) Network centrality
4) Assortativity and similarity in complex networks
5) Spectral graph theory
6) Properties of random graphs
7) Properties of real-world random graphs
8) Community structure
9) Possibility of community detection
10) Processes on networks
11) Network motifs and graphlets
12) Introduction to sparsity
13) Application of bounded expansion
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