Cross-domain aspect term extraction using pre-trained language models with pre-training and fine-tuning strategy
As an important subtask of fine-grained sentiment analysis, aspect term extraction (ATE) aims to identify aspect terms within user-generated comments. ATE supervised learning approaches are heavily based on the availability of annotated data with token-level labels. However, obtaining these annotati...
保存先:
| 主要な著者: | , , , |
|---|---|
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
KeAi Communications Co. Ltd.
2026-03-01
|
| シリーズ: | Data Science and Management |
| 主題: | |
| オンライン･アクセス: | http://www.sciencedirect.com/science/article/pii/S2666764925000384 |
| タグ: |
タグなし, このレコードへの初めてのタグを付けませんか!
|