Name
Abstract | ||
|---|---|---|
This work takes the lead to study the aspect-level sentiment classification in the domain adaptation scenario. Given a document of any domains, the model needs to figure out the sentiments with respect to fine-grained aspects in the documents. Two main challenges exist in this problem. One is to build a robust document modeling across domains; the other is to mine the domain-speci... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TAFFC.2019.2897093 | IEEE Transactions on Affective Computing |
Keywords | DocType | Volume |
Adaptation models,Neural networks,Task analysis,Computational modeling,Probabilistic logic,Social networking (online),Semantics | Journal | 12 |
Issue | ISSN | Citations |
3 | 1949-3045 | 2 |
PageRank | References | Authors |
0.37 | 25 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min Yang | 1 | 155 | 41.56 |
| Wenpeng Yin | 2 | 387 | 23.87 |
| qiang qu | 3 | 83 | 12.15 |
| Wenting Tu | 4 | 85 | 9.48 |
| Shen Ying | 5 | 73 | 23.48 |
| Xiaojun Chen | 6 | 1298 | 107.51 |