| 大会名称 |
| 2018年 ソサイエティ大会 |
| 大会コ－ド |
| 2018S |
| 開催年 |
|
2018
|
| 発行日 |
|
2018/8/28
|
| セッション番号 |
|
BS-7
|
| セッション名 |
|
Network and Service Design, Control and Management
|
| 講演日 |
|
2018/9/11
|
| 講演場所(会議室等) |
|
自然科学本館 2F 203講義室
|
| 講演番号 |
|
BS-7-1
|
| タイトル |
|
A Proposal of Sparse-Modeling based Approach for Betweenness Centrality Estimation
|
| 著者名 |
|
◎Ryotaro Matsuo, Ryo Nakamura, Hiroyuki Ohsaki,
|
| キーワード |
|
Sparse Modeling, Betweenness Centrality, Network Flow Problem, Minimum Link Flow Problem, Shortest-Path Tree
|
| 抄録 |
|
In recent years, a statistical approach for estimating unobserved model parameters from a small number of observations utilizing the sparsity of model parameters called sparse modeling have been extensively studied. In our previous work, we have shown the effectiveness of sparse modeling for a network flow problem called minimum link flow problem. This paper extends our sparse-modeling based approach to a more complex problem --- estimation of betweenness centrality, which is one of the major graph indices. In this paper, we present a sparse-modeling based solution for betweenness centrality estimation. Betweenness centralities of all nodes in an undirected graph are estimated from shortest-path trees, each of which is obtained as the solution for the minimum link flow problem formulated as the l_1-norm minimization problem.
|
| 本文pdf |
|
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|
