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Paper Abstract and Keywords
Presentation 2021-09-09 11:35
On the Effectiveness of Breadth-First Search for Influence Maximization on Unknown Networks
Yuki Wakisaka, Ryotaro Matsuo (Kwansei Gakuin Univ.), Sho Tsugawa (Tsukuba Univ.), Hiroyuki Ohsaki (Kwansei Gakuin Univ.) CQ2021-42
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, the influence maximization problem for unknown networks has received much attention. The problem aims to identify a small set of influential nodes only from a partial structure of the network obtained by network sampling. To achieve efficient influence propagation on unknown networks, it is necessary to determine the sampling strategy and the number of sample nodes appropriately. We have analytically clarified the relationship between the sample size and the number of activated nodes when random sampling is used as the sampling strategy through theoretical analysis. In this paper, we extend our previous analysis to derive the expected number of activated nodes when breadth-first search, which is a typical crawl-based sampling strategy, is used. Furthermore, we comparatively investigate the effectiveness of random sampling and breadth-first search in influence maximization for unknown networks through several numerical examples. The results show that sampling with breadth-first search requires a smaller sample size to achieve the same number of activated nodes than random sampling.
Keyword (in Japanese) (See Japanese page) 
(in English) Influence Maximization / Information Diffusion / Social Networks / Unknown Networks / Network Sampling / BFS (Breadth-First Search) / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 173, CQ2021-42, pp. 29-34, Sept. 2021.
Paper # CQ2021-42 
Date of Issue 2021-09-02 (CQ) 
ISSN Print edition: ISSN 0913-5685  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)
Download PDF CQ2021-42

Conference Information
Committee CQ MIKA  
Conference Date 2021-09-09 - 2021-09-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Wireless Communications Quality, 6G, IoT, Resource Management, Wireless Transmission, Cross layer Technologies, etc. 
Paper Information
Registration To CQ 
Conference Code 2021-09-CQ-MIKA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) On the Effectiveness of Breadth-First Search for Influence Maximization on Unknown Networks 
Sub Title (in English)  
Keyword(1) Influence Maximization  
Keyword(2) Information Diffusion  
Keyword(3) Social Networks  
Keyword(4) Unknown Networks  
Keyword(5) Network Sampling  
Keyword(6) BFS (Breadth-First Search)  
Keyword(7)  
Keyword(8)  
1st Author's Name Yuki Wakisaka  
1st Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
2nd Author's Name Ryotaro Matsuo  
2nd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
3rd Author's Name Sho Tsugawa  
3rd Author's Affiliation University of Tsukuba (Tsukuba Univ.)
4th Author's Name Hiroyuki Ohsaki  
4th Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
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Speaker
Date Time 2021-09-09 11:35:00 
Presentation Time 20 
Registration for CQ 
Paper # IEICE-CQ2021-42 
Volume (vol) IEICE-121 
Number (no) no.173 
Page pp.29-34 
#Pages IEICE-6 
Date of Issue IEICE-CQ-2021-09-02 


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