Information Extraction using Convolution Neural Network

An awesome summary generator for text articles!
Explore the docs »

View Demo · Report Bug · Request Feature

Table of Contents

• About the Project
• Getting Started
  • Prerequisites
  • Installation
• Contributor
• License
• Contact
• Referrences

About The Project

Information Extraction has been one of the important task in Natural Language Processing (NLP). The said task have been accomplished by using sophisticated machine learning algorithms like Nave Bayes. We will try to approach the problem using Convolutional Neural Networks (CNN) with least possible hyper parameter tuning on pre trained word vectors. It is expected that we can reach our goal with considerable results using CNN that will be computationally much efficient than the traditional approaches.

Getting Started

Prerequisites

Programming Language

Python 3.6

• pip

sudo apt install python3-pip

• gensim

pip install gensim

• nltk

pip install nltk

• numpy

pip install numpy

• tensorflow

pip install tensorflow

• keras

pip install Keras

IDE Used:

• Jupyter Notebook

Installation

git clone https://github.com/mihirsam/Information-Extraction-using-CNN.git

Contributor

• Mihir
• Chandni Agarwal
• Sweta Agarwal

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Mihir - [email protected]

Project Link: https://github.com/mihirsam/Information-Extraction-using-CNN

Referrences

• Convolutional Neural Networks for Text Classification by David S. Batista
• Convolutional Neural Networks for Sentence Classification by Yoon Kim