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Artificial Neural Networks: A Comparative Analysis for the Purposes of Text Classification

Connell, Glenn (2019) Artificial Neural Networks: A Comparative Analysis for the Purposes of Text Classification. Masters thesis, Dublin, National College of Ireland.

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Abstract

Natural Language Processing (NLP) is an area of great interest within both academia and industry, that has, with the advent of Web 2.0, quietly been gathering an even larger following. One of the key components of many NLP applications, text classification, may be considered one of the largest sub-fields within NLP. Traditional text classifiers tended to be restricted in effectiveness due to their reliance upon human-designed features such as dictionaries. Machine learning has since risen to prominence over traditional methods. Within this paper a comparative analysis has been performed comparing two algorithms, Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN), finding CNN to be the superior approach.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 11 Oct 2019 12:03
Last Modified: 11 Oct 2019 12:03
URI: https://norma.ncirl.ie/id/eprint/3843

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