Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Absa Pytorch | 1,782 | 4 months ago | 91 | mit | Python | |||||
Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析,使用PyTorch实现。 | ||||||||||
Aspect Based Sentiment Analysis | 413 | 9 months ago | 8 | August 01, 2021 | 33 | apache-2.0 | Python | |||
💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow) | ||||||||||
Td Lstm | 252 | 6 years ago | Python | |||||||
Attention-based Aspect-term Sentiment Analysis implemented by tensorflow. | ||||||||||
Nlp Papers | 248 | 3 years ago | ||||||||
Papers I have read, mainly about NLP. Welcome everyone to supplement in issue. | ||||||||||
Doc Han Att | 193 | 6 years ago | 5 | Jupyter Notebook | ||||||
Hierarchical Attention Networks for Chinese Sentiment Classification | ||||||||||
Datastories Semeval2017 Task4 | 171 | 5 years ago | 8 | mit | Python | |||||
Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis". | ||||||||||
Sa Papers | 108 | 5 years ago | ||||||||
📄 Deep Learning 中 Sentiment Analysis 論文統整與分析 😀😡☹️😭🙄🤢 | ||||||||||
Absa_keras | 103 | 4 years ago | 3 | Python | ||||||
Keras Implementation of Aspect based Sentiment Analysis | ||||||||||
Hierarchical Sentiment | 96 | 4 years ago | 1 | mit | Python | |||||
Hierarchical Models for Sentiment Analysis in Pytorch | ||||||||||
Ian | 85 | 4 years ago | 4 | mit | Python | |||||
A TensorFlow implementation for "Interactive Attention Networks for Aspect-Level Sentiment Classification" |
This is the code for the paper:
VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis
Quoc-Tuan Truong and Hady W. Lauw
Presented at AAAI 2019
We provide:
If you find the code and data useful in your research, please cite:
@inproceedings{truong2019vistanet,
title={Vistanet: Visual aspect attention network for multimodal sentiment analysis},
author={Truong, Quoc-Tuan and Lauw, Hady W},
booktitle={Proceedings of the AAAI conference on artificial intelligence},
volume={33},
number={01},
pages={305--312},
year={2019}
}
python data_preprocess.py
VistaNet
:python train.py --hidden_dim 50 --att_dim 100 --num_images 3 --batch_size 32 --learning_rate 0.001 --num_epochs 20
Questions and discussion are welcome: www.qttruong.com