# Complex Networks

(
Murata Tsuyoshi
)

Mon 5-6Session W833

Credits Lecture:2 Practice:0 Experiment:0 / code:76053

Update : 2011/12/23

Access Index :

Fall Semester

- Outline of lecture
- 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

networks. - Purpose of lecture
- 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. - Plan of lecture
- 1. introduction

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

14. summary - Textbook and reference
- Textbook:

Networks, An Introduction

http://www-personal.umich.edu/~mejn/networks-an-introduction/

Reference:

Networks, Crowds, and Markets

http://www.cs.cornell.edu/home/kleinber/networks-book/ - Related and/or prerequisite courses
- Discrete Structures and Algorithms
- Evaluation
- Based on 2 or 3 times of assignments
- Comments from lecturer
- Please visit the following site for more information about this lecture.

http://www.ai.cs.titech.ac.jp/lecture/cn/