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Named entity recognition in unstructured text.

KERETNA, SARA 2016, Named entity recognition in unstructured text., PhD. thesis, GTP Research, Deakin University.

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Title Named entity recognition in unstructured text.
Author KERETNA, SARA
Institution Deakin University
School GTP Research
Faculty Institute for Intelligent Systems Research and Innovation
Degree type Research doctorate
Degree name PhD.
Thesis advisor Creighton Douglas
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Date submitted 2016-06
Keyword(s) Named Entity Recognition
Digital data
Medical records
text mining
Software development
Summary The thesis introduces a set of machine learning techniques that enhance the extraction of Named Entities from informal and unstructured free text.
Language eng
Field of Research 099999 - Engineering not elsewhere classified 100%
Socio Economic Objective 970109 - Expanding Knowledge in Engineering 100%
Description of original 164 pages : tables, figures, some coloured.
Copyright notice ┬ęThe Author. All Rights Reserved
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30089371

Document type: Thesis
Collections: Higher degree theses (full text)
Open Access Collection
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Created: Fri, 25 Nov 2016, 10:37:01 EST by Deb Gray

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.