Multimodal sentiment analysis using hierarchical fusion with context modeling
Multimodal sentiment analysis is a very actively growing field of research. A promising area of opportunity in this field is to improve the multimodal fusion mechanism. We present a novel feature fusion strategy that proceeds in a hierarchical fashion, first fusing the modalities two in two and only...
Saved in:
Main Authors: | Majumder, Navonil, Hazarika, Devamanyu, Gelbukh, Alexander, Cambria, Erik, Poria, Soujanya |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/139583 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Multimodal sentiment analysis : addressing key issues and setting up the baselines
by: Poria, Soujanya, et al.
Published: (2020) -
A novel context-aware multimodal framework for persian sentiment analysis
by: Dashtipour, Kia, et al.
Published: (2022) -
Sentic maxine: Multimodal affective fusion and emotional paths
by: Hupont, I., et al.
Published: (2014) -
Sentic API: A common-sense based API for concept-level sentiment analysis
by: Cambria, Erik, et al.
Published: (2017) -
Ensemble application of ELM and GPU for real-time multimodal sentiment analysis
by: Tran, Ha-Nguyen, et al.
Published: (2020)