Paper Abstract and Keywords |
Presentation |
2021-03-19 10:40
Study of Event Monitoring Technique Using Machine Learning for IT Operations
-- Study of AI for IT Ops -- Takashi Tameshige, Yasuyuki Tamai, Mineyoshi Masuda, Koichi Murayama (Hitachi) SC2020-34 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In the normal event arrival confirmation which is an IT operator business, IT operator confirms that IT system is running normally with all the visual and double check. We developed a monitoring technology for IT events that utilized machine learning. Normal events have ample features that are covered by the training data because of the abundance of past events. We focused on the features and monitored all monitoring items using machine learning. This monitoring technology consists of a monitoring item extraction technique that calculates similarity of all monitoring items and extracts only the highest value, and pretreatment automation technology to remove noise from the message body. By applying this technology, we have improved the coverage of monitoring items and have been able to automate normal event monitoring operations. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
IT Operator / IT Operation / normal event / monitoring / machine learning / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 434, SC2020-34, pp. 7-12, March 2021. |
Paper # |
SC2020-34 |
Date of Issue |
2021-03-12 (SC) |
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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SC2020-34 |
Conference Information |
Committee |
SC |
Conference Date |
2021-03-19 - 2021-03-19 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
SC |
Conference Code |
2021-03-SC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Study of Event Monitoring Technique Using Machine Learning for IT Operations |
Sub Title (in English) |
Study of AI for IT Ops |
Keyword(1) |
IT Operator |
Keyword(2) |
IT Operation |
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normal event |
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monitoring |
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machine learning |
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1st Author's Name |
Takashi Tameshige |
1st Author's Affiliation |
Hitachi Ltd. (Hitachi) |
2nd Author's Name |
Yasuyuki Tamai |
2nd Author's Affiliation |
Hitachi Ltd. (Hitachi) |
3rd Author's Name |
Mineyoshi Masuda |
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Hitachi Ltd. (Hitachi) |
4th Author's Name |
Koichi Murayama |
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Hitachi Ltd. (Hitachi) |
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Speaker |
Author-1 |
Date Time |
2021-03-19 10:40:00 |
Presentation Time |
30 minutes |
Registration for |
SC |
Paper # |
SC2020-34 |
Volume (vol) |
vol.120 |
Number (no) |
no.434 |
Page |
pp.7-12 |
#Pages |
6 |
Date of Issue |
2021-03-12 (SC) |
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