| Presentation | 2023-09-06 Rating Prediction of Multi-aspect Reviews Using Multi-task Learning Framework Masaki Takeo, Shinnosuke Kawasaki, Kazutaka Shimada, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, we propose a method for rating prediction tasks in review documents. Existing models for predicting the rating scores assigned to each aspect were often developed separately. However, there is a relationship among aspects. Therefore, we apply a multi-task learning framework to our prediction models. We name this method ``Simultaneous Learning.''We evaluate our model with a review dataset about a game software domain. Each review document contains six-level rating scores for seven aspects of the game software. We utilize BERT as the base model for the prediction. Our model simultaneously learns the parameters of seven BERTs for seven aspects. In addition, we compare two types of input data for the rating prediction task: all sentences and selected sentences. Experimental results show the effectiveness of our simultaneous learning model in the multi-aspect rating prediction. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Sentiment Analysis / Review Analysis / Simultaneous Learning / Parameter Sharing / Rating Predicition |
| Paper # | NLC2023-4 |
| Date of Issue | 2023-08-30 (NLC) |
| Conference Information | |
| Committee | NLC |
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| Conference Date | 2023/9/6(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Osaka Metropolitan University. Nakamozu Campus. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | The 20th Text Analytics Symposium |
| Chair | Mitsuo Yoshida(Univ. of Tsukuba) |
| Vice Chair | Hiroki Sakaji(Univ. of Tokyo) / Takeshi Kobayakawa(NHK) |
| Secretary | Hiroki Sakaji(rinna) / Takeshi Kobayakawa(Hiroshima Univ. of Economics) |
| Assistant | Kanjin Takahashi(Sansan) / Yasuhiro Ogawa(Nagoya Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Natural Language Understanding and Models of Communication |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Rating Prediction of Multi-aspect Reviews Using Multi-task Learning Framework |
| Sub Title (in English) | |
| Keyword(1) | Sentiment Analysis |
| Keyword(2) | Review Analysis |
| Keyword(3) | Simultaneous Learning |
| Keyword(4) | Parameter Sharing |
| Keyword(5) | Rating Predicition |
| 1st Author's Name | Masaki Takeo |
| 1st Author's Affiliation | Kyushu Institute of Technology(Kyutech) |
| 2nd Author's Name | Shinnosuke Kawasaki |
| 2nd Author's Affiliation | Kyushu Institute of Technology(Kyutech) |
| 3rd Author's Name | Kazutaka Shimada |
| 3rd Author's Affiliation | Kyushu Institute of Technology(Kyutech) |
| Date | 2023-09-06 |
| Paper # | NLC2023-4 |
| Volume (vol) | vol.123 |
| Number (no) | NLC-176 |
| Page | pp.pp.18-23(NLC), |
| #Pages | 6 |
| Date of Issue | 2023-08-30 (NLC) |