TY  - THES
A1  - Demirel, Saner
T1  - Spectral Graph Convolutional Networks for Part-of-Speech Tagging
N2  - Part-of-Speech tagging is the process of assigning words with similar grammatical properties to a part of speech (PoS). In the English language, PoS-tagging algorithms generally reach very high accuracy. This thesis undertakes the task to test against these accuracies in PoS-tagging as a qualitative measure in classification capabilities for a recently developed neural network model, called graph convolutional network (GCN). The novelty proposed in this thesis is to translate a corpus into a graph as a direct input for the GCN. The experiments in this thesis serve as a proof of concept with room for improvements.
Y1  - 2017
UR  - https://kola.opus.hbz-nrw.de/frontdoor/index/index/docId/1508
UR  - https://nbn-resolving.org/urn:nbn:de:kola-15080
ER  -