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Paper Abstract and Keywords
Presentation 2025-07-31 15:30
Directional Community Detection Based on Node Distances in Multi-Platform Graphs
Suzuka Okamoto, Tsuyoshi Yamashita, Kunitake Kaneko (Keio Univ.) IN2025-16
Abstract (in Japanese) (See Japanese page) 
(in English) In community detection on multi-platform graphs constructed from different backgrounds, it is desirable that common nodes across graphs belong to the same community. Such alignment enables the detection of highly overlapping communities with consistent expansion directions, facilitating the discovery of new insights and enabling applications such as recommendation systems. However, existing methods are often sensitive to structural differences caused by non-common nodes, making it difficult to extract communities with high overlap across graphs.
This paper proposes a local community detection method that does not depend on the presence of non-common nodes. Instead, it focuses on the similarity of distance relationships among common nodes across graphs. Starting from a shared seed node, the method expands the community based on distances, and evaluates the degree of overlap between the resulting communities. Experimental results show that the proportion of common nodes included in the same community across graphs increases by up to 0.5 compared to existing methods.
Keyword (in Japanese) (See Japanese page) 
(in English) Graph / Multi-Platform Graph / Community Detection / Network Alignment / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 137, IN2025-16, pp. 31-36, July 2025.
Paper # IN2025-16 
Date of Issue 2025-07-24 (IN) 
ISSN 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 IN2025-16

Conference Information
Committee CCS IN  
Conference Date 2025-07-31 - 2025-08-01 
Place (in Japanese) (See Japanese page) 
Place (in English) Global Research Center for Food & Medical Innovation, Hokkaido Univ 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network Science, Future Network, Cloud/SDN/Virtualization, Contents Delivery/Contents Exchange, and others 
Paper Information
Registration To IN 
Conference Code 2025-07-CCS-IN 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Directional Community Detection Based on Node Distances in Multi-Platform Graphs 
Sub Title (in English)  
Keyword(1) Graph  
Keyword(2) Multi-Platform Graph  
Keyword(3) Community Detection  
Keyword(4) Network Alignment  
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1st Author's Name Suzuka Okamoto  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Tsuyoshi Yamashita  
2nd Author's Affiliation Keio University (Keio Univ.)
3rd Author's Name Kunitake Kaneko  
3rd Author's Affiliation Keio University (Keio Univ.)
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Speaker Author-1 
Date Time 2025-07-31 15:30:00 
Presentation Time 25 minutes 
Registration for IN 
Paper # IN2025-16 
Volume (vol) vol.125 
Number (no) no.137 
Page pp.31-36 
#Pages 6 
Date of Issue 2025-07-24 (IN) 

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