RELATION EXTRACTION USING DEEP LEARNING METHODS - A SURVEY

Abstract
Relation extraction has an important role in extracting structured information from unstructured raw text. This task is a crucial ingredient in numerous information extraction systems seeking to mine structured facts from text. Nowadays, neural networks play an important role in the task of relation extraction. The traditional non deep learning models require feature engineering. Deep Learning models such as Convolutional Neural Networks and Long Short Term Memory networks require less feature engineering than non-deep learning models. Relation Extraction has the potential of employing deep learning models with the creation of huge datasets using distant supervision. This paper surveys the current trend in Relation Extraction using Deep Learning models.

Authors
C A Deepa1, P C ReghuRaj2, Ajeesh Ramanujan3
Government Engineering College Sreekrishnapuram, India1,2, College of Engineering Trivandrum, India3

Keywords
Relation Extraction, Deep Learning, LSTM, CNN, word Embeddings
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 9 , Issue: 3 )
Date of Publication :
April 2019
DOI :

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