gereka / text_gcn

Graph Convolutional Networks for Text Classification. AAAI 2019

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text_gcn

The implementation of Text GCN in our paper:

Liang Yao, Chengsheng Mao, Yuan Luo. "Graph Convolutional Networks for Text Classification." In 33rd AAAI Conference on Artificial Intelligence (AAAI-19)

Require

Python 2.7 or 3.6

Tensorflow >= 1.4.0

Reproduing Results

  1. Run python remove_words.py 20ng

  2. Run python build_graph.py 20ng

  3. Run python train.py 20ng

  4. Change 20ng in above 3 command lines to R8, R52, ohsumed and mr when producing results for other datasets.

Example input data

  1. /data/20ng.txt indicates document names, training/test split, document labels. Each line is for a document.

  2. /data/corpus/20ng.txt contains raw text of each document, each line is for the corresponding line in /data/20ng.txt

About

Graph Convolutional Networks for Text Classification. AAAI 2019


Languages

Language:Yacc 99.8%Language:Python 0.2%