| Item type |
文献 / Documents(1) |
| 公開日 |
2020-04-10 |
| アクセス権 |
|
|
アクセス権 |
open access |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版社版DOI |
|
|
|
関連識別子 |
https://doi.org/10.18178/ijmlc.2020.10.1.912 |
|
|
関連名称 |
10.18178/ijmlc.2020.10.1.912 |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| タイトル |
|
|
タイトル |
Classification of Smartphone Application Reviews Using Small Corpus Based on Bidirectional LSTM Transformer |
| 著者 |
松本, 和幸
土屋, 誠司
コジマ, タクミ
コンドウ, ヒロヤ
吉田, 稔
北, 研二
|
| 抄録 |
|
|
内容記述 |
This paper provides the classification of the review texts on a smartphone application posted on social media. We propose a high performance binary classification method (positive/negative) of review texts, which uses the bidirectional long short-term memory (biLSTM) self-attentional Transformer and is based on the distributed representations created by unsupervised learning of a manually labelled small review corpus, dictionary, and an unlabeled large review corpus. The proposed method obtained higher accuracy as compared to the existing methods, such as StarSpace or the Bidirectional Encoder Representations from Transformer (BERT). |
| キーワード |
|
|
主題 |
Attention mechanism |
| キーワード |
|
|
主題 |
review classification |
| キーワード |
|
|
主題 |
small corpus |
| キーワード |
|
|
主題 |
transformer |
| 書誌情報 |
en : International Journal of Machine Learning and Computing
巻 10,
号 1,
p. 148-157,
発行日 2020-01
|
| 収録物ID |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
20103700 |
| 権利情報 |
|
|
権利情報 |
© 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0). |
| EID |
|
|
識別子 |
363265 |
| 言語 |
|
|
言語 |
eng |
ijmlc_10_1_148.pdf (21.1 MB)
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