2007 Fiscal Year Final Research Report Summary
Mathematical Modeling of Complex Networks by Using a Learning Approach
| Project/Area Number |
18500113
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Nagoya Institute of Technology |
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Principal Investigator |
NAKANO Ryohei Nagoya Institute of Technology, Dept of Computer Science, Professor (90324467)
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| Co-Investigator(Kenkyū-buntansha) |
SAITO Kazumi University of Shizuoka, School of Administration and Informatics, Professor (80379544)
KITAKOSHI Daisuke Nagoya Institute of Technology, Dept of Computer Science, Assistant Professor (50378238)
KIMURA Masahiro Ryukoku University, Dept of Electronics and Informatics, Ryukoku University Dept of Electronics and Informatics (10396153)
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| Project Period (FY) |
2006 – 2007
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| Keywords | complex network / network growth / information diffusion / mixture of communities / forest fire model / blog-roll / link prediction |
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| Research Abstract |
The aim of this research is to analysis the Internet which keeps growing rapidly as a complex network, to find a mathematical model for the growing network, and to explain its behavior by using the mathematical model. Firstly we proposed a method which extracts communities from social network data. Secondly, after defining an influence maximization problem for information diffusion in a social network, we proposed a very fast method to solve the problem by making good use of bond-percolation. Finally, we proposed a method which estimates probable link generations for network growth. All the proposed methods were evaluated for real large-scale networks.
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