抄録
The main task we address in our research is classification of text using fine-grained attitude labels. The developed@AM system relies on the compositionality principle and a novel approach based on the rules elaborated for semantically distinct verb classes. The evaluation of our method on 1000 sentences, that describe personal experiences, showed promising results: average accuracy on the fine grained level (14 labels) was 62%, on the middle level (7 labels) - 71%, and on the top level (3 labels) - 88%.
| 本文言語 | English |
|---|---|
| ホスト出版物のタイトル | Coling 2010 - 23rd International Conference on Computational Linguistics, Proceedings of the Conference |
| ページ | 806-814 |
| ページ数 | 9 |
| 巻 | 2 |
| 出版ステータス | Published - 2010 |
| 外部発表 | はい |
| イベント | 23rd International Conference on Computational Linguistics, Coling 2010 - Beijing 継続期間: 2010 8月 23 → 2010 8月 27 |
Other
| Other | 23rd International Conference on Computational Linguistics, Coling 2010 |
|---|---|
| City | Beijing |
| Period | 10/8/23 → 10/8/27 |
ASJC Scopus subject areas
- 言語および言語学
- 計算理論と計算数学
- 言語学および言語