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| Presentation | 2020-10-01 13:15 A Study on Recovering Network Topology with Missing Links using Sparse Modeling Ryotaro Matsuo, Hiroyuki Ohsaki (Kwansei Gakuin Univ.)  IA2020-3 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In recent years, sparse modeling, which is a statistical approach, has been applied to many practical problems mostly in the fields of signal processing and image processing, and a dictionary construction method and a sparse representation for network topology with sparse modeling have been proposed in the field of information networking. We believe that a dictionary for network topologies can be utilized for various purposes. In this paper, we investigate how the network topology with missing links can be recovered using a dictionary for network topologies constructed with sparse modeling. Specifically, we propose a method called TRSM (Topology Recovery with Sparse Modeling) that recovers missing links using a dictionary constructed from many teaching network topologies using the overcomplete dictionary construction algorithm called K-SVD algorithm. Furthermore, through experiments, we investigate how accurately the randomly deleted links from a network can be recovered with TRSM. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Link Prediction / Sparse Modeling / Sparse Representation / Overcomplete Dictionary / Network Topology / l_0-norm Minimization Problem / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 177, IA2020-3, pp. 10-13, Oct. 2020. | |
| Paper # | IA2020-3 | |
| Date of Issue | 2020-09-24 (IA) | |
| 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 | IA2020-3 |
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| Conference Information | |
| Committee | IA |
| Conference Date | 2020-10-01 - 2020-10-01 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | IA2020 - Workshop on Internet Architecture and Applications 2020 |
| Paper Information | |
| Registration To | IA |
| Conference Code | 2020-10-IA |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study on Recovering Network Topology with Missing Links using Sparse Modeling |
| Sub Title (in English) | |
| Keyword(1) | Link Prediction |
| Keyword(2) | Sparse Modeling |
| Keyword(3) | Sparse Representation |
| Keyword(4) | Overcomplete Dictionary |
| Keyword(5) | Network Topology |
| Keyword(6) | l_0-norm Minimization Problem |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Ryotaro Matsuo |
| 1st Author's Affiliation | Kwansei Gakuin University (Kwansei Gakuin Univ.) |
| 2nd Author's Name | Hiroyuki Ohsaki |
| 2nd Author's Affiliation | Kwansei Gakuin University (Kwansei Gakuin Univ.) |
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| Speaker | Author-1 |
| Date Time | 2020-10-01 13:15:00 |
| Presentation Time | 25 minutes |
| Registration for | IA |
| Paper # | IA2020-3 |
| Volume (vol) | vol.120 |
| Number (no) | no.177 |
| Page | pp.10-13 |
| #Pages | 4 |
| Date of Issue | 2020-09-24 (IA) |
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