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Paper Abstract and Keywords
Presentation 2014-03-07 14:15
Graph Entropy as a Measure for Estimating Robustness of Centrality Measures against Imperfections of Graphs
Masanori Ishino (Osaka Univ.), Sho Tsugawa (Univ. of Tsukuba), Hiroyuki Ohsaki (Kwansei Gakuin Univ.), Toru Hasegawa (Osaka Univ.) CQ2013-101
Abstract (in Japanese) (See Japanese page) 
(in English) Complex network analysis has been actively pursued to investigate the characteristics of large-scale complex networks. Graphs used for complex network analysis generally contain several types of noises. Hence, investigating the effects of noises on centrality measures and also validating the accuracy of centrality measures used in complex network analyses is one of the important research topics in the area of complex networks. To clarify the accuracy of the centrality measures, we address a research question: how can we estimate the robustness of centrality measures in a graph from topological structure of the graph? We focus on graph entropy as a possible measure for estimating the robustness of centrality measures. In this paper, we experimentally investigate the effectiveness of graph entropy for estimating the robustness of centrality measures. Consequently, we show that (1) the graph entropy is useful for estimating the robustness of four types of centrality measures against noises due to random addition and deletion of nodes and links, and (2) the graph entropy is useful for estimating the robustness of four types of popular centrality measures (i.e., closeness, betweenness, degree, and eigenvector centralities).
Keyword (in Japanese) (See Japanese page) 
(in English) Complex Network / Centrality Measures / Robustness / Graph Entropy / Social Network Analysis / Eigenvector Centrality / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 471, CQ2013-101, pp. 71-76, March 2014.
Paper # CQ2013-101 
Date of Issue 2014-02-27 (CQ) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF CQ2013-101

Conference Information
Committee CQ MVE IE IMQ CEA  
Conference Date 2014-03-06 - 2014-03-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Beppu International Convention Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Five senses media, Food media, Social media, Multimedia, Virtual Environment, Image encoding, Cloud, Mobile, Network, and their quality and reliability，General area 
Paper Information
Registration To CQ 
Conference Code 2014-03-CQ-MVE-IE-IMQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Graph Entropy as a Measure for Estimating Robustness of Centrality Measures against Imperfections of Graphs 
Sub Title (in English) * 
Keyword(1) Complex Network  
Keyword(2) Centrality Measures  
Keyword(3) Robustness  
Keyword(4) Graph Entropy  
Keyword(5) Social Network Analysis  
Keyword(6) Eigenvector Centrality  
Keyword(7)  
Keyword(8)  
1st Author's Name Masanori Ishino  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Sho Tsugawa  
2nd Author's Affiliation University of Tsukuba (Univ. of Tsukuba)
3rd Author's Name Hiroyuki Ohsaki  
3rd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
4th Author's Name Toru Hasegawa  
4th Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2014-03-07 14:15:00 
Presentation Time 25 minutes 
Registration for CQ 
Paper # CQ2013-101 
Volume (vol) vol.113 
Number (no) no.471 
Page pp.71-76 
#Pages 6 
Date of Issue 2014-02-27 (CQ) 

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