Seminar on Computational Learning and
Adaptation
A Model of Network Growth with Communities
Kazumi Saito
Intelligent Communication Laboratory
NTT Communication Science Laboratories
2-4 Hikaridai, Seika-cho, Soraku-gun
Kyoto 619-0237 JAPAN
saito@cslab.kecl.ntt.co.jp
In this talk, we propose a model for the growth of networks and an
associated learning algorithm. Unlike the conventional scale-free
approaches, the model incorporates community structure, which is an
important characteristic of many real-world networks, including the
World Wide Web. Experimental studies reveal that the model exhibits
a degree distribution with a power-law tail and that the learning
method can precisely estimate the probability of new link creation
from data without community information. Moreover, by introducing a
measure of dynamic hub degrees, it can predict the change of hub
degrees between communities.
This talk describes joint work with Masahiro Kimura and Naonori Ueda.
Date: Thursday, May 2
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Time: 4:15-5:30PM
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Place: Cordura 100
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