| Title: | OS19-1 Extraction of Irrelevant Sentences from Online Hotel Reviews |
|---|---|
| Publication: | ICAROB2020 |
| Volume: | 25 |
| Pages: | 407-410 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2020.OS19-1 |
| Author(s): | Shogo Watanabe, Masaharu Hirota, Tetsuya Oda |
| Publication Date: | January 13, 2020 |
| Keywords: | Review analysis, Hotel reviews, Classification, Supervised learning method |
| Abstract: | Many reviews of hotels have been posted on review sites such as TripAdvisor and Yelp. Many tourists select a hotel to reserve using their ratings and reviews. Although containing useful information, those reviews may also contain useless information, which reduces their readability. Removing irrelevant sentences from those reviews can improve their readability. This paper proposes a method to extract irrelevant sentences from a review. Our approach uses a supervised learning method to classify sentences into relevant and irrelevant. We demonstrate the performance of our proposed method by evaluation experiment using the TripAdvisor dataset. |
| PDF File: | https://alife-robotics.co.jp/members2020/icarob/data/html/data/OS/OS19/OS19-1.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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