Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Visual Qa | 476 | 5 years ago | 24 | mit | Python | |||||
[Reimplementation Antol et al 2015] Keras-based LSTM/CNN models for Visual Question Answering | ||||||||||
Ccks2019_el | 210 | 4 years ago | 3 | Python | ||||||
CCKS 2019 中文短文本实体链指比赛技术创新奖解决方案 | ||||||||||
Nlp Model | 184 | 4 years ago | 2 | Python | ||||||
Learning and practice | ||||||||||
Aspect Extraction | 119 | 2 years ago | apache-2.0 | Python | ||||||
Aspect extraction from product reviews - window-CNN+maxpool+CRF, BiLSTM+CRF, MLP+CRF | ||||||||||
Gcae | 98 | 5 years ago | 11 | Python | ||||||
Spacy Pretrain Polyaxon | 64 | 2 years ago | 3 | Python | ||||||
Example using Polyaxon to experiment with pre-training spaCy | ||||||||||
Pytorch_bert_elmo_example | 62 | 3 years ago | 5 | Python | ||||||
A text classification example with Bert/ELMo/GloVe in pytorch | ||||||||||
Tf_sentence_similarity_cnn | 53 | 6 years ago | 4 | Python | ||||||
Text Classification Pytorch | 47 | a year ago | Python | |||||||
Implementation of papers for text classification task on SST-1/SST-2 | ||||||||||
Iclassifier | 40 | 2 years ago | 1 | Python | ||||||
reference pytorch code for intent classification |
@inproceedings{DBLP:conf/acl/LiX18,
author = {Wei Xue and Tao Li},
title = {Aspect Based Sentiment Analysis with Gated Convolutional Networks},
booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational
Linguistics, {ACL} 2018, Melbourne, Australia, July 15-20, 2018, Volume
1: Long Papers},
pages = {2514--2523},
year = {2018},
crossref = {DBLP:conf/acl/2018-1},
url = {https://aclanthology.info/papers/P18-1234/p18-1234},
timestamp = {Thu, 12 Jul 2018 14:15:56 +0200},
biburl = {https://dblp.org/rec/bib/conf/acl/LiX18},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Download glove or word2vec file and change the path in w2v.py correspondingly.
python -m run -lr 1e-2 -batch-size 32 -verbose 1 -model CNN_Gate_Aspect -embed_file glove -r_l r -epochs 13
python -m run -lr 1e-2 -batch-size 32 -verbose 1 -model CNN_Gate_Aspect -embed_file glove -r_l r -year 14 -epochs 5
python -m run -lr 5e-3 -batch-size 32 -verbose 1 -model CNN_Gate_Aspect -embed_file glove -r_l r -year 14 -epochs 6 -atsa
python -m run -lr 5e-3 -batch-size 32 -verbose 1 -model CNN_Gate_Aspect -embed_file glove -r_l l -year 14 -epochs 5 -atsa