The 18th European Conference on Machine Learning (ECML) and the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD)

Mining Large Graphs: Laws and Tools

author: Jure Leskovec, Computer Science Department, Stanford University
published: Jan. 28, 2008, recorded: September 2007, views: 5359

Slides

Slides
0:00	Mining Large Graphs
0:22	Networks –Social and Technological
1:40	Examples of Networks
2:36	Networks of the Real-world (1)
3:59	Networks of the Real-world (2)
4:35	Mining Social Network Data
5:46	Networks as Phenomena
6:43	Models and Laws of Networks
7:46	Networks: Rich Data
8:54	Networks: A Matter of Scale
9:56	Networks: Scale Matters
11:10	Structure vs. Process
11:47	Structure of Networks
11:59	Diffusion in Networks
12:20	Tutorial outline
13:07	Mining Large GraphsPart 1: Structure and models of networks
13:11	Part 1: Outline
13:22	Part 1.1: Structural properties
13:24	Traditional approach
13:53	Motivation: New approach (1)
14:24	Motivation: New approach (2)
14:41	Graphs and networks
15:29	Small-world effect (1)
17:54	Small-world effect (2)
18:50	Small-world effect (3)
19:59	Degree distributions (1)
21:34	Degree distributions (2)
25:05	Poisson vs. Scale-free network
25:55	Network resilience (1)
26:48	Network resilience (2)
27:29	Poisson vs. Scale-free network
27:36	Network resilience (2)
28:05	Community structure
28:51	Spectral properties
29:08	What about evolving graphs?
29:55	Networks over time: Densification (1)
30:27	Networks over time: Densification (2)
32:22	Densification & degree distribution
32:49	Shrinking diameters
34:38	Properties hold in many graphs
35:16	Part 1.2: Models
35:23	Properties hold in many graphs
36:10	Part 1.2: Models
36:27	1.2 Models: Outline
36:38	(Erdos-Renyi) Random graph
37:34	Properties of random graphs
39:08	Evolution of a random graph
39:12	Subgraphs in random graphs
40:26	Random graphs: conclusion
42:27	Exponential random graphs (p* models)
43:36	Exponential random graphs
45:28	Small-world model (1)
46:17	Small-world model (2)
47:06	Small-world model (3)
48:53	Preferential attachment (1)
50:20	Preferential attachment (2)
51:03	Edge copying model
53:02	Community guided attachment (1)
54:54	Community guided attachment (2)
55:29	Community guided attachment (1)
55:38	Community guided attachment (2)
55:51	Community guided attachment (1)
56:05	Community guided attachment (2)
56:23	Community guided attachment (1)
56:58	Community guided attachment (2)
56:59	Forest Fire Model (1)
58:30	Forest Fire Model (2)
59:02	Forest Fire Model (1)
59:32	Forest Fire Model (2)
59:34	Forest Fire Model (3)
60:05	Forest Fire Model (4)

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