Basic knowledge for analyzing network data is introduced.
Topics include metrics of networks, common properties of
real networks, algorithms for processing networks, models of
networks, visualization of networks, and tools for analyzing
The purpose of this lecture is to learn basic knowledge for analyzing and
modeling networks, such as 1) fundamentals of networks, 2) network algorithms,
3) network models, and 4) processes on networks.
2. tools for analyzing networks
3. fundamentals (1) mathematics of networks
4. fundamentals (2) measures and metrics
5. fundamentals (3) the large-scale structure of networks
6. network algorithms (1) representation
7. network algorithms (2) matrix algorithms
8. network algorithms (3) graph partitioning
9. network models (1) random graphs
10. network models (2) network formation
11. network models (3) small-world model
12. processes on networks (1) percolation
13. processes on networks (2) epidemics
Networks, An Introduction
Networks, Crowds, and Markets
Discrete Structures and Algorithms
Based on 2 or 3 times of assignments
Please visit the following site for more information about this lecture.