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Paper Abstract and Keywords
Presentation 2024-07-30 09:50
A Study on Machine Learning Approach for Creating Graphs with Given Graph Statistics
Aoba Iwaki (Nagaoka Univ. of Tech.), Sho Tsugawa (Univ. of Tsukuba), Akiko Manada (Nagaoka Univ. of Tech.), Kohei Watabe (Saitama Univ.) IN2024-23
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, machine learning techniques have been proposed to analyze the mathematical properties of graphs and create graphs for applications such as social network analysis and molecular discovery. However, these machine learning methods face challenges, including the need for large datasets and the lack of mathematical guarantees on the range of features of the generated graphs.This paper proposes a machine learning-based graph analysis founded on the classical Barabási-Albert (BA) model. We confirmed that the proposed method can generate graphs by specifying cluster coefficients with extremely high accuracy, and that the generated graphs generally maintain the scale-free property of the BA Model.
Keyword (in Japanese) (See Japanese page) 
(in English) Network / Graph / LSTM / Conditional Generation / Machine Learning / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 139, IN2024-23, pp. 77-82, July 2024.
Paper # IN2024-23 
Date of Issue 2024-07-22 (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 IN2024-23

Conference Information
Committee IN CCS  
Conference Date 2024-07-29 - 2024-07-30 
Place (in Japanese) (See Japanese page) 
Place (in English) Moerenuma Park Glass Pyramid 
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 2024-07-IN-CCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Machine Learning Approach for Creating Graphs with Given Graph Statistics 
Sub Title (in English)  
Keyword(1) Network  
Keyword(2) Graph  
Keyword(3) LSTM  
Keyword(4) Conditional Generation  
Keyword(5) Machine Learning  
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Keyword(8)  
1st Author's Name Aoba Iwaki  
1st Author's Affiliation Nagaoka University of Technology (Nagaoka Univ. of Tech.)
2nd Author's Name Sho Tsugawa  
2nd Author's Affiliation University of Tsukuba (Univ. of Tsukuba)
3rd Author's Name Akiko Manada  
3rd Author's Affiliation Nagaoka University of Technology (Nagaoka Univ. of Tech.)
4th Author's Name Kohei Watabe  
4th Author's Affiliation Saitama University (Saitama Univ.)
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Speaker Author-1 
Date Time 2024-07-30 09:50:00 
Presentation Time 25 minutes 
Registration for IN 
Paper # IN2024-23 
Volume (vol) vol.124 
Number (no) no.139 
Page pp.77-82 
#Pages 6 
Date of Issue 2024-07-22 (IN) 

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