Detecting Invisible Relevant Persons in a Homogeneous Social Network

Authors:
Yoshiharu Maeno;Kiichi Ito;Yukio Ohsawa
Affiliations:
Graduate School of Systems Management, Tsukuba University, 3-29-11 Otsuka, Bunkyo-ku, Tokyo, 112-0012, Japan;Graduate School of Media and Governance, Keio University, 5322 Endo, Fujisawa-shi, Kanagawa 252-8520, Japan;School of Engineering, the University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8563, Japan
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Year:
2007

Citing 4
Cited 0

Structure in the Enron Email Dataset

Computational & Mathematical Organization Theory
Emergent Information Technologies and Enabling Policies for Counter-Terrorism (IEEE Press Series on Computational Intelligence)

Emergent Information Technologies and Enabling Policies for Counter-Terrorism (IEEE Press Series on Computational Intelligence)
Chance Discoveries in Real World Decision Making: Data-based Interaction of Human intelligence and Artificial Intelligence (Studies in Computational Intelligence)

Chance Discoveries in Real World Decision Making: Data-based Interaction of Human intelligence and Artificial Intelligence (Studies in Computational Intelligence)
Human-interactive annealing for turning threat to opportunity in technology development

ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops

Quantified Score

Hi-index	0.00

Visualization

Abstract

An algorithm to detect invisible relevant persons in a homogeneous social network is studied with computer simulation. The network is effective as a model for contemporary inter-working terrorists where large hub persons do not exist. Absense of large hub persons results in that the observed communication flow is also homogeneous. Clues regarding invisible relevant persons are hardly found in communication records. This task is, therefore, generally difficult. We demonstrate that our algorithm identifies the portion of the market baskets representing communication records, where invisible relevant persons are likely to be hidden, with good precision.