monk1337/Graph-Neural-networks-for-NLP
Graph Neural networks for NLP
This project offers a collection of research papers focused on using Graph Neural Networks to enhance Natural Language Processing tasks. It helps researchers and NLP practitioners understand how to process and analyze textual data by representing it as graphs, leading to more nuanced insights. It takes academic research as input and provides frameworks and methodologies for advanced text analysis.
No commits in the last 6 months.
Use this if you are an NLP researcher or practitioner looking for cutting-edge techniques to improve text classification, sentiment analysis, relation extraction, or knowledge graph alignment.
Not ideal if you are looking for ready-to-use software or code implementations without diving into academic papers and underlying algorithms.
Stars
27
Forks
5
Language
—
License
—
Category
Last pushed
Oct 08, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/monk1337/Graph-Neural-networks-for-NLP"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
kyzhouhzau/NLPGNN
1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and...
IndexFziQ/GNN4NLP-Papers
A list of recent papers about Graph Neural Network methods applied in NLP areas.
qipeng/gcn-over-pruned-trees
Graph Convolution over Pruned Dependency Trees Improves Relation Extraction (authors' PyTorch...
kenqgu/Text-GCN
A PyTorch implementation of "Graph Convolutional Networks for Text Classification." (AAAI 2019)
daiquocnguyen/Graph-Transformer
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)