Name
Title | ||
|---|---|---|
Modelling Context with Graph Convolutional Networks for Aspect-based Sentiment Analysis |
Abstract | ||
|---|---|---|
Aspect-based sentiment analysis is a fine-grained natural language processing task that aims to predict a specific target's sentiment polarity in its context. Existing researches mainly focus on the exploration of the interaction between the sentiment polarity of aspects and contexts. Models based on the self-attention mechanism can fully explore the syntactic structure of sentences. In contrast, ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICDMW53433.2021.00031 | 2021 International Conference on Data Mining Workshops (ICDMW) |
Keywords | DocType | ISSN |
Sentiment analysis,Analytical models,Conferences,Semantics,Syntactics,Data models,Data mining | Conference | 2375-9232 |
ISBN | Citations | PageRank |
978-1-6654-2427-1 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maoyuan Zhang | 1 | 0 | 0.34 |
| Jieqiong Zhang | 2 | 0 | 0.34 |
| Lisha Liu | 3 | 0 | 0.34 |