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| Paper Abstract and Keywords | ||
| Presentation | 2021-03-15 13:25 Graph Structure Optimization Using Genetic Algorithms Hiroki Tajiri, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.)  NLP2020-59 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | There are many large and complex networks in the real world. These networks are modeled as graphs and analyzed using a variety of features. The algebraic connectivity is one of the features that measures how well a graph is connected, and is defined by the second smallest eigenvalue of the Laplacian matrix of the graph. This paper considers the problem of maximizing the algebraic connectivity of a given graph by adding a specified number of edges. We propose a genetic algorithm for approximately solving this problem and evaluate its performance through experiments. We also apply the proposed method to the problem of maximizing the clustering coefficient, which represents how strongly the neighbors of a vertex are connected with each other, and evaluate its performance through experiments. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | algebraic connectivity / clustering coefficient / maximization / genetic algorithm / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 430, NLP2020-59, pp. 23-28, March 2021. | |
| Paper # | NLP2020-59 | |
| Date of Issue | 2021-03-08 (NLP) | |
| 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 | NLP2020-59 |
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| Conference Information | |
| Committee | NLP MSS |
| Conference Date | 2021-03-15 - 2021-03-16 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | MSS, NLP, Work In Progress (MSS only), and etc. |
| Paper Information | |
| Registration To | NLP |
| Conference Code | 2021-03-NLP-MSS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Graph Structure Optimization Using Genetic Algorithms |
| Sub Title (in English) | |
| Keyword(1) | algebraic connectivity |
| Keyword(2) | clustering coefficient |
| Keyword(3) | maximization |
| Keyword(4) | genetic algorithm |
| Keyword(5) | |
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| 1st Author's Name | Hiroki Tajiri |
| 1st Author's Affiliation | Okayama University (Okayama Univ.) |
| 2nd Author's Name | Tsuyoshi Migita |
| 2nd Author's Affiliation | Okayama University (Okayama Univ.) |
| 3rd Author's Name | Norikazu Takahashi |
| 3rd Author's Affiliation | Okayama University (Okayama Univ.) |
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| Speaker | Author-1 |
| Date Time | 2021-03-15 13:25:00 |
| Presentation Time | 25 minutes |
| Registration for | NLP |
| Paper # | NLP2020-59 |
| Volume (vol) | vol.120 |
| Number (no) | no.430 |
| Page | pp.23-28 |
| #Pages | 6 |
| Date of Issue | 2021-03-08 (NLP) |
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