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Refrenced paper : HDLTex: Hierarchical Deep Learning for Text Classification <https://arxiv.org/abs/1709.08267>
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|Pic|
Increasingly large document collections require improved information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which has become an important application for supervised learning. Recently the performance of traditional supervised classifiers has degraded as the number of documents has increased. This is because along with growth in the number of documents has come an increase in the number of categories. This paper approaches this problem differently from current document classification methods that view the problem as multi-class classification. Instead we perform hierarchical classification using an approach we call Hierarchical Deep Learning for Text classification (HDLTex). HDLTex employs stacks of deep learning architectures to provide specialized understanding at each level of the document hierarchy.
.. code:: bash
pip install HDLTex
.. code:: bash
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:
.. code:: bash
pip -r install requirements.txt
Or
.. code:: bash
pip3 install -r requirements.txt
Or:
.. code:: bash
conda install --file requirements.txt
If the above command does not work, use the following:
.. code:: bash
sudo -H pip install -r requirements.txt
Link of dataset: |Data|
Web of Science Dataset
WOS-11967 <http://dx.doi.org/10.17632/9rw3vkcfy4.2>
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This dataset contains 11,967 documents with 35 categories which include 7 parents categories.
Web of Science Dataset
WOS-46985 <http://dx.doi.org/10.17632/9rw3vkcfy4.2>
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This dataset contains 46,985 documents with 134 categories which include 7 parents categories.
Web of Science Dataset
WOS-5736 <http://dx.doi.org/10.17632/9rw3vkcfy4.2>
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This dataset contains 5,736 documents with 11 categories which include 3 parents categories.
General:
Instruction Documents <https://www.python.org/>
__Instruction Documents <https://www.tensorflow.org/install/install_linux>
__.Instruction Documents <http://scikit-learn.org/stable/install.html>
__Instruction Documents <https://keras.io/>
__Instruction Documents <https://www.scipy.org/install.html>
__NVIDIA’s documentation <https://developer.nvidia.com/cuda-toolkit>
__.NVIDIA drivers associated with CUDA Toolkit 8.0 <http://www.nvidia.com/Download/index.aspx>
__.NVIDIA’s documentation <https://developer.nvidia.com/cudnn>
__.::
$ sudo apt-get install libcupti-dev
Global Vectors for Word Representation
(GLOVE <https://nlp.stanford.edu/projects/glove/>
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For CNN and RNN you need to download and linked the folder location to GLOVE
Send an email to kk7nc@virginia.edu
.. code:: bash
@inproceedings{Kowsari2018HDLTex,
author={Kowsari, Kamran and Brown, Donald E and Heidarysafa, Mojtaba and Meimandi, Kiana Jafari and Gerber, Matthew S and Barnes, Laura E},
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}
}
.. |DOI| image:: https://img.shields.io/badge/DOI-10.1109%2FICMLA.2017.0--134-blue :target: https://doi.org/10.1109/ICMLA.2017.0-134 .. |travis| image:: https://travis-ci.org/kk7nc/HDLTex.svg?branch=master :target: https://travis-ci.org/kk7nc/HDLTex .. |wercker status| image:: https://app.wercker.com/status/24a123448ba8764b257a1df242146b8e/s/master :target: https://app.wercker.com/project/byKey/24a123448ba8764b257a1df242146b8e .. |Join the chat at https://gitter.im/HDLTex| image:: https://badges.gitter.im/Join%20Chat.svg :target: https://gitter.im/HDLTex/Lobby?source=orgpage .. |appveyor| image:: https://ci.appveyor.com/api/projects/status/github/kk7nc/HDLTex?branch=master&svg=true :target: https://ci.appveyor.com/project/kk7nc/hdltex .. |arXiv| image:: https://img.shields.io/badge/arXiv-1709.08267-red.svg?style=flat :target: https://arxiv.org/abs/1709.08267 .. |RG| image:: https://img.shields.io/badge/ResearchGate-HDLTex-blue.svg?style=flat :target: https://www.researchgate.net/publication/319968747_HDLTex_Hierarchical_Deep_Learning_for_Text_Classification .. |Binder| image:: https://mybinder.org/badge.svg :target: https://mybinder.org/v2/gh/kk7nc/HDLTex/master .. |license| image:: https://img.shields.io/github/license/mashape/apistatus.svg?maxAge=2592104 :target: https://github.com/kk7nc/HDLTex/blob/master/LICENSE .. |Data| image:: https://img.shields.io/badge/DOI-10.17632/9rw3vkcfy4.6-blue.svg?style=flat :target: http://dx.doi.org/10.17632/9rw3vkcfy4.6 .. |Pic| image:: docs/HDLTex.png :alt: HDLTex as both Hierarchy lavel are DNN .. |twitter| image:: https://img.shields.io/twitter/url/http/shields.io.svg?style=social :target: https://twitter.com/intent/tweet?text=HDLTex:%20Hierarchical%20Deep%20Learning%20for%20Text%20Classification%0aGitHub:&url=https://github.com/kk7nc/HDLTex&hashtags=DeepLearning,Text_Classification,classification,MachineLearning,deep_neural_networks
.. |Download| image:: https://pepy.tech/badge/hdltex :target: https://pepy.tech/project/hdltex