Paper Abstract and Keywords |
Presentation |
2023-03-13 16:35
Lifelog Data Analyses of SNS Users Based on Supervised Learning to Forecast the Number of Bookmarks of A Post Komei Arasawa, Shun Matsukawa, Nobuyuki Sugio, Naofumi Wada, Hiroki Matsuzaki (Hokkaido Univ. of Sci.) LOIS2022-56 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
It is an important issue to establish how to produce and transmit a post that triggers people's interest, in marketing and other activities using social network. In particular, we need a technology that forecasts the posts that users would be interested in and identifies the factors. This paper proposes a method that forecasts whether or not a user would bookmark a post that he/she sees from now on, based on learning the features the posts are bookmarked by the user. In addition, it evaluates the performance of the method and analyzes the factors that affect bookmark-behavior of each user. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Machine Learning / Like / Twitter / Gradient Boosting Decision Tree / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 423, LOIS2022-56, pp. 72-76, March 2023. |
Paper # |
LOIS2022-56 |
Date of Issue |
2023-03-06 (LOIS) |
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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LOIS2022-56 |
Conference Information |
Committee |
LOIS |
Conference Date |
2023-03-13 - 2023-03-14 |
Place (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
LOIS |
Conference Code |
2023-03-LOIS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Lifelog Data Analyses of SNS Users Based on Supervised Learning to Forecast the Number of Bookmarks of A Post |
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Keyword(1) |
Machine Learning |
Keyword(2) |
Like |
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Twitter |
Keyword(4) |
Gradient Boosting Decision Tree |
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Keyword(6) |
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1st Author's Name |
Komei Arasawa |
1st Author's Affiliation |
Hokkaido University of Science (Hokkaido Univ. of Sci.) |
2nd Author's Name |
Shun Matsukawa |
2nd Author's Affiliation |
Hokkaido University of Science (Hokkaido Univ. of Sci.) |
3rd Author's Name |
Nobuyuki Sugio |
3rd Author's Affiliation |
Hokkaido University of Science (Hokkaido Univ. of Sci.) |
4th Author's Name |
Naofumi Wada |
4th Author's Affiliation |
Hokkaido University of Science (Hokkaido Univ. of Sci.) |
5th Author's Name |
Hiroki Matsuzaki |
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Hokkaido University of Science (Hokkaido Univ. of Sci.) |
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Speaker |
Author-1 |
Date Time |
2023-03-13 16:35:00 |
Presentation Time |
25 minutes |
Registration for |
LOIS |
Paper # |
LOIS2022-56 |
Volume (vol) |
vol.122 |
Number (no) |
no.423 |
Page |
pp.72-76 |
#Pages |
5 |
Date of Issue |
2023-03-06 (LOIS) |
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