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| Presentation | 2021-09-16 09:35 Using GAN-BERT to Detect Unfair Sentences in Terms of Service Takumi Kondo, Yasuhiro Ogawa, Katsuhiko Toyama (Nagoya Univ.)  NLC2021-7 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Although the terms of service (ToS) tend to be skipped because of their large number of articles, some of them may be potentially unfair to users. In this paper, we propose a method for automatically detecting unfair articles in ToS so that users can check them efficiently. The previous studies used linear SVM for the automatic detection in Japanese ToS, and it performed undersampling to eliminate imbalance in the training data to improve classification performance. However, the classification performance is not satisfactory. In this paper, we use GAN-BERT, a learning model that extends BERT with semi-supervised GANs, to use a small number of labeled ToS and easily available unlabeled ToS for training, and show higher classification performance. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Terms of Service / Unfair article / GAN-BERT / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 178, NLC2021-7, pp. 5-10, Sept. 2021. | |
| Paper # | NLC2021-7 | |
| Date of Issue | 2021-09-09 (NLC) | |
| 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 | NLC2021-7 |
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| Conference Information | |
| Committee | NLC |
| Conference Date | 2021-09-16 - 2021-09-16 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | The 18th Text Analytics Symposium |
| Paper Information | |
| Registration To | NLC |
| Conference Code | 2021-09-NLC |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Using GAN-BERT to Detect Unfair Sentences in Terms of Service |
| Sub Title (in English) | |
| Keyword(1) | Terms of Service |
| Keyword(2) | Unfair article |
| Keyword(3) | GAN-BERT |
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| Keyword(8) | |
| 1st Author's Name | Takumi Kondo |
| 1st Author's Affiliation | Nagoya University (Nagoya Univ.) |
| 2nd Author's Name | Yasuhiro Ogawa |
| 2nd Author's Affiliation | Nagoya University (Nagoya Univ.) |
| 3rd Author's Name | Katsuhiko Toyama |
| 3rd Author's Affiliation | Nagoya University (Nagoya Univ.) |
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| Speaker | Author-1 |
| Date Time | 2021-09-16 09:35:00 |
| Presentation Time | 25 minutes |
| Registration for | NLC |
| Paper # | NLC2021-7 |
| Volume (vol) | vol.121 |
| Number (no) | no.178 |
| Page | pp.5-10 |
| #Pages | 6 |
| Date of Issue | 2021-09-09 (NLC) |
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