6533b820fe1ef96bd12796ef

RESEARCH PRODUCT

Classification with Multiple Classes using Naïve Bayes and Text Generation with a Small Data Set using a Recurrent Neural Network

Tore Elias Gjervik Reiten

subject

IKT590VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420

description

Master's thesis Information- and communication technology IKT590 - University of Agder 2017 In this thesis, text classification and text generation are explored using only a small data set and many classes. This thesis experiments with text classification, and show how it is able to find the most similar output compared to the input even with thousands of classes. Furthermore, text generation is explored on a small data set to create a unique output. By using Na¨ıve Bayes text classifier combined with a Recurrent Neural Network language-model, it is possible to use new deviations as input before an original suggestion for a measure is generated as the output

yearjournalcountryeditionlanguage
2017-01-01
http://hdl.handle.net/11250/2455012