Stable Deterministic Crystallization for Discovering Hidden Hubs

Author

Maeno, Yoshiharu ; Ohsawa, Yukio

Author_Institution

Tsukuba Univ., Tokyo

Volume

2

fYear

2006

fDate

8-11 Oct. 2006

Firstpage

1393

Lastpage

1398

Abstract

Experts of chance discovery have recognized a new class of problems where the previous methods fail to reveal a latent structure behind observation. There are invisible events which play an important role in the dynamics of visible events. A hidden hub person (an invisible leader) in a communication network is a typical example. This paper presents a stable deterministic crystallization algorithm for discovering such hidden hub events. The algorithm is evaluated with the test data generated from a large scale-free random network. It is demonstrated that precision for discovering the hidden hub events remains as high as 80% to 100%, regardless of the prior knowledge and the network structure.

Keywords

data mining; graph theory; pattern clustering; KeyGraph; chance discovery; communication network; deterministic crystallization algorithm; graph structure; hidden hub discovery; hidden hub person; invisible events; invisible leader; latent structure; random network; Atmosphere; Collaboration; Communication networks; Crystallization; Cybernetics; Data visualization; Decision making; Humans; Terrorism; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on

Conference_Location

Taipei

Print_ISBN

1-4244-0099-6

Electronic_ISBN

1-4244-0100-3

Type

conf

DOI

10.1109/ICSMC.2006.384911

Filename

4274045