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Paper Abstract and Keywords
Presentation 2021-12-17 12:55
[Short Paper] Study on the Separability of Aggregated Multilayer Networks
Rong Wang, Yuki Wakisaka, Ryotaro Matsuo, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2021-42
Abstract (in Japanese) (See Japanese page) 
(in English) Many real networks consist of heterogeneous networks with different properties, and these heterogeneous networks interact with each other. Most existing studies of networks focus on single-layer networks. However, in recent years, analysis methods and algorithms for multilayer networks have begun to be studied. Even if a network is originally a multilayer network consisting of heterogeneous networks, it is commonly treated as a single-layer network when analyzing data. If it is possible to reconstruct the each layer network of the original multilayer network from the single-layer network in which the multilayer network is aggregated, it is expected that more detailed analysis of the multilayer network will be possible using conventional network analysis methods. In this paper, given a single-layer network obtained by aggregating multilayer networks, we investigate the extent to which the original multilayer network can be reconstructed from the single-layer network. Specifically, when a two-layer network is aggregated into a single-layer network, through experiments, we investigate how accurately the aggregated single-layer network can be separated into the original two-layer network from the partial information about the original network (the subnetworks of each layer of the original network).
Keyword (in Japanese) (See Japanese page) 
(in English) Graph Separation / Link Classification / Multilayer Networks / Heterogeneous Networks / Graph Neural Networks / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 300, IA2021-42, pp. 60-62, Dec. 2021.
Paper # IA2021-42 
Date of Issue 2021-12-09 (IA) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee IN IA  
Conference Date 2021-12-16 - 2021-12-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Higashi-Senda campus, Hiroshima Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Performance Analysis and Simulation, Robustness, Traffic and Throughput Measurement, Quality of Service (QoS) Control, Congestion Control, Overlay Network/P2P, IPv6, Multicast, Routing, DDoS, etc. 
Paper Information
Registration To IA 
Conference Code 2021-12-IN-IA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on the Separability of Aggregated Multilayer Networks 
Sub Title (in English)  
Keyword(1) Graph Separation  
Keyword(2) Link Classification  
Keyword(3) Multilayer Networks  
Keyword(4) Heterogeneous Networks  
Keyword(5) Graph Neural Networks  
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Keyword(7)  
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1st Author's Name Rong Wang  
1st Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
2nd Author's Name Yuki Wakisaka  
2nd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
3rd Author's Name Ryotaro Matsuo  
3rd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
4th Author's Name Hiroyuki Ohsaki  
4th Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
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Speaker Author-1 
Date Time 2021-12-17 12:55:00 
Presentation Time 15 minutes 
Registration for IA 
Paper # IA2021-42 
Volume (vol) vol.121 
Number (no) no.300 
Page pp.60-62 
#Pages
Date of Issue 2021-12-09 (IA) 


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