kenqgu/Text-GCN
A PyTorch implementation of "Graph Convolutional Networks for Text Classification." (AAAI 2019)
This project helps you categorize text documents quickly and accurately, even with limited training data. You provide a collection of documents and their assigned categories (or some of them), and it outputs a model that can predict categories for new documents. It also generates meaningful representations for your words and documents. This is ideal for data scientists, NLP practitioners, or researchers needing robust text classification.
129 stars. No commits in the last 6 months.
Use this if you need to classify documents into predefined categories and want a method that performs well with less labeled training data.
Not ideal if your task involves generating new text, translating languages, or answering open-ended questions from text.
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129
Forks
25
Language
Python
License
MIT
Category
Last pushed
Jun 27, 2020
Commits (30d)
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