Name
Abstract | ||
|---|---|---|
Metaphors are frequently used to constitute strong emotional expressions within human communication. The sentiment of a metaphor is decided by many factors, including its context, target, cultural background, etc. Previous relevant work mainly focuses on modeling the context of metaphor, however, the importance of cultural factors is not fully discussed, even in cross-lingual systems. Our work builds a system to perform Chinese metaphor sentiment analysis. It considers both context and target of a metaphor, as well as Chinese culture-related knowledge. The system organizes cultural factors in the form of cultural attribute vectors. It models the influence of context and target by using an attention-based Long Short-Term Memory network (LSTM). |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.neucom.2019.03.087 | Neurocomputing |
Keywords | Field | DocType |
Metaphor,Knowledge,Context,Attention,LSTM | Cognitive science,Sentiment analysis,Emotional expression,Artificial intelligence,Human communication,Metaphor,Mathematics,Machine learning | Journal |
Volume | ISSN | Citations |
352 | 0925-2312 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chang Su | 1 | 6 | 3.20 |
| Junchao Li | 2 | 4 | 4.18 |
| Ying Peng | 3 | 0 | 1.35 |
| Yijiang Chen | 4 | 3 | 2.11 |