Thesis Title:
An empirical investigation into the properties of standard word embeddings
Author: Salomon Kabongo Kabenamualu
Supervised by: Professor Etienne Barnard
From: North-West University, South Africa
AIMS Centre: AIMS South Africa
AIMS Program: Structured Masters
Academic Year: 2018-2019
Defense Date: 05/23/2019
Abstract:
The embedding of word sequences into continuous vector spaces has been one of the most important developments in Natural Language Processing in the recent past. Such embeddings have found application in areas such as Automatic Speech Recognition, Machine Translation, Sentiment Analysis and many more. This essay reviews the various mechanisms that have been proposed for the calculation of word embeddings, investigates popular toolkits and embedding matrices that are available in the public domain, and experiments with one or more selected implementations to better understand their characteristics.
Keywords: NLP, Embeddings, Neural Networks, Machine Learning.
Thesis Document: