Particle competition for complex network community detection

1. Particle competition for complex network community detection Author: Marcos G. Quiles, Liang Zhao, Ronaldo L. Alonso, and RoseliA.Romero An Interdisciplinary Journal of Nonlinear Science

2. Outline • The concept -Randomness and Determinism -Competition • The method • The experiments

3. Randomness and Determinism • Human decision making is a tradoff between randomness and determinism. • When one has complete knowledge about a specific subject, a deterministic choice can be made, on the other hand, a random decision is made when one knows nothing about it.

4. Competition • Competition is a natural process widely observed in living sharing limited resources.

5. The method • In the proposed model, particles walk in the network and compete with each other that each of them tries to possess as many nodes as possible. • The process continues until a dynamical equilibrium(when each community has only one particle) state is reached.

6. Each particle has two variables

7. Each node has three variables

9. Each particle has probability pdet to take deterministic moving and 1-pdet to take random moving • Random moving: randomly selects a neighbor to visit(immediately return to the node visited at last iteration is not allowed ,unless the node’s degree is 1). • Deterministic moving: allows the particle always to visit a node that is already owned by it.

10. 1 2 3 5 4 8 6 7 9

11. A particle encounters one of the following three situation s for each visit 1.If a node being visited by a particle has no owner yet. 2.If a node being visited by a particle belong to the particle itself. 3. If anode being visited by a particle belong to another particle.

12. At beginning, K particles are put at K randomly chosen vertices of a network. • Each particle has initial potential • Each node has initial potential • Still at this moment, all vertices are free

13. T=0 1 2 3 5 4 8 6 7 9 13

14. The Experiments