Refrenced paper : HDLTex: Hierarchical Deep Learning for Text Classification
There are git RMDL in this repository; to clone all the needed files, please use:
git clone --recursive https://github.com/kk7nc/HDLTex.git
The primary requirements for this package are Python 3 with Tensorflow. The requirements.txt file contains a listing of the required Python packages; to install all requirements, run the following:
pip -r install requirements.txt
Or
pip3 install -r requirements.txt
Or:
conda install --file requirements.txt
If the above command does not work, use the following:
sudo -H pip install -r requirements.txt
Documentation:
Datasets for HDLTex:
Linke of dataset: DOI: 10.17632/9rw3vkcfy4.6
Web of Science Dataset WOS-11967
This dataset contains 11,967 documents with 35 categories which include 7 parents categories.
Web of Science Dataset WOS-46985
This dataset contains 46,985 documents with 134 categories which include 7 parents categories.
Web of Science Dataset WOS-5736
This dataset contains 5,736 documents with 11 categories which include 3 parents categories.
Requirment :
General:
Python 3.5 or later see Instruction Documents
TensorFlow see Instruction Documents.
scikit-learn see Instruction Documents
Keras see Instruction Documents
scipy see Instruction Documents
GPU:
CUDA® Toolkit 8.0. For details, see NVIDIA's documentation.
The NVIDIA drivers associated with CUDA Toolkit 8.0.
cuDNN v6. For details, see NVIDIA's documentation.
GPU card with CUDA Compute Capability 3.0 or higher.
The libcupti-dev library,
To install this library, issue the following command:
$ sudo apt-get install libcupti-dev
Feature Extraction:
Global Vectors for Word Representation (GLOVE)
For CNN and RNN you need to download and linked the folder location to GLOVE
Send an email to [email protected]
@inproceedings{Kowsari2018HDLTex,
author={K. Kowsari and D. E. Brown and M. Heidarysafa and K. Jafari Meimandi and M. S. Gerber and L. E. Barnes},
booktitle={2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA)},
title={HDLTex: Hierarchical Deep Learning for Text Classification},
year={2017},
pages={364-371},
doi={10.1109/ICMLA.2017.0-134},
month={Dec}
}