Paper Abstract and Keywords |
Presentation |
2021-10-14 13:00
Network Structure and Information Diffusion Models in Social Networking Service Improve Information Retention in Liquid State Machines through Neuronal Activity Modulation Hiromichi Furuya, Toshikazu Samura (Yamaguchi Univ) CAS2021-22 NLP2021-20 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
A Liquid State Machine (LSM) realizes information processing by retaining past information in its recursive structure. Thus, the information retention capacity is important, but the information is gradually lost with time. On the other hand, it is considered that information which is spread once on Social Networking Service (SNS) is hard to be erased. In this study, we constructed LSMs that reproduce the network structure and the information diffusion of SNS as neuronal activity modulation, and confirmed that they improve the accuracy of a delayed readout task. Consequently, we suggest that the network structure and information diffusion of SNS improve the information retention capacity of LSMs. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Liquid State Machine / Social Networking Service / Network Structure / Information Diffusion / Information Retention / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 197, NLP2021-20, pp. 29-34, Oct. 2021. |
Paper # |
NLP2021-20 |
Date of Issue |
2021-10-07 (CAS, 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) |
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CAS2021-22 NLP2021-20 |
Conference Information |
Committee |
CAS NLP |
Conference Date |
2021-10-14 - 2021-10-15 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
NLP |
Conference Code |
2021-10-CAS-NLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Network Structure and Information Diffusion Models in Social Networking Service Improve Information Retention in Liquid State Machines through Neuronal Activity Modulation |
Sub Title (in English) |
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Liquid State Machine |
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Social Networking Service |
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Network Structure |
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Information Diffusion |
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Information Retention |
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1st Author's Name |
Hiromichi Furuya |
1st Author's Affiliation |
Yamaguchi University (Yamaguchi Univ) |
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Toshikazu Samura |
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Yamaguchi University (Yamaguchi Univ) |
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Speaker |
Author-1 |
Date Time |
2021-10-14 13:00:00 |
Presentation Time |
25 minutes |
Registration for |
NLP |
Paper # |
CAS2021-22, NLP2021-20 |
Volume (vol) |
vol.121 |
Number (no) |
no.196(CAS), no.197(NLP) |
Page |
pp.29-34 |
#Pages |
6 |
Date of Issue |
2021-10-07 (CAS, NLP) |
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