Deep Learning applied to NLP

TL;DR

This paper explains how convolutional neural networks, originally used in computer vision, are adapted and applied to natural language processing tasks, highlighting their variations and recent successes.

Contribution

It provides an overview of CNN architectures, their variations, and their application to NLP, bridging the gap between vision and language processing.

Findings

CNNs have achieved interesting results in NLP tasks

Different CNN variations are effective for various NLP problems

The paper clarifies the basics and adaptations of CNNs for NLP

Abstract

Convolutional Neural Network (CNNs) are typically associated with Computer Vision. CNNs are responsible for major breakthroughs in Image Classification and are the core of most Computer Vision systems today. More recently CNNs have been applied to problems in Natural Language Processing and gotten some interesting results. In this paper, we will try to explain the basics of CNNs, its different variations and how they have been applied to NLP.