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Paper Abstract and Keywords
Presentation 2024-12-20 13:30
Graph Reduction Method Combining Sampling and Crawling with High Connectivity
Sora Satoh, Tsuyoshi Yamashita, Kunitake Kaneko (Keio Univ.) IN2024-72
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, the use of entire graphs has become increasingly challenging due to security concerns, highlighting the importance of understanding relationships between data through reduced graphs.Reduced graphs that allow traversal of adjacency information, including nodes near a user’s nodes of interest and nodes from various communities, are particularly valuable.However, existing reduction methods often exhibit significant bias toward specific communities, making such reductions difficult to achieve.To address this issue, this study proposes a method that leverages Random Walk (RW)-based sampling and crawling enhanced to facilitate transitions to community boundary nodes, enabling the creation of such reduced graphs.Specifically, the proposed approach employs ego network density—a measure of the density of a subgraph composed of a node and its neighbors—to perform crawling that more effectively reaches boundary nodes.Additionally, by switching between this crawling method and a transition probability that favors high-degree nodes, the sampling method ensures better connectivity with the crawling graph.In experiments, we partitioned the original graph into communities and evaluated the ease of reaching each community in both the original and reduced graphs using RW flow.The results showed that the cosine similarity, a measure of resemblance, was approximately 0.2 higher than existing methods, demonstrating that the reduced graph maintains accessibility to communities similar to the original graph.
Keyword (in Japanese) (See Japanese page) 
(in English) sampling / crawling / ego network / community / random walk / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 312, IN2024-72, pp. 99-106, Dec. 2024.
Paper # IN2024-72 
Date of Issue 2024-12-12 (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)
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Conference Information
Committee IN IA  
Conference Date 2024-12-19 - 2024-12-20 
Place (in Japanese) (See Japanese page) 
Place (in English) KIITO 
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, CCN, ICN, Multicast, Routing, Security, etc. 
Paper Information
Registration To IN 
Conference Code 2024-12-IN-IA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Graph Reduction Method Combining Sampling and Crawling with High Connectivity 
Sub Title (in English)  
Keyword(1) sampling  
Keyword(2) crawling  
Keyword(3) ego network  
Keyword(4) community  
Keyword(5) random walk  
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1st Author's Name Sora Satoh  
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 2024-12-20 13:30:00 
Presentation Time 25 minutes 
Registration for IN 
Paper # IN2024-72 
Volume (vol) vol.124 
Number (no) no.312 
Page pp.99-106 
#Pages 8 
Date of Issue 2024-12-12 (IN) 

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