Keyword and named entity recognition on air traffic control (ATC) data

Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/79003

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DC Field	Value	Language
dc.contributor.author	Thia, Jeremy Ming Xuan
dc.date.accessioned	2019-11-25T01:13:21Z
dc.date.available	2019-11-25T01:13:21Z
dc.date.issued	2019
dc.identifier.uri	http://hdl.handle.net/10356/79003
dc.description.abstract	This project will explore several NLP tasks to perform named entity recognition on Air Traffic Control data, to be specific Air Traffic conversations. We will use a Bi-LSTM-CNN-CRF based custom named entity system to detect the entities. A demonstration of the working model will be presented as well.	en_US
dc.format.extent	35 p.	en_US
dc.language.iso	en	en_US
dc.rights	Nanyang Technological University
dc.subject	Engineering::Computer science and engineering::Computing methodologies::Document and text processing	en_US
dc.subject	Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence	en_US
dc.title	Keyword and named entity recognition on air traffic control (ATC) data	en_US
dc.type	Final Year Project (FYP)	en_US
dc.contributor.supervisor	Chng Eng Siong	en_US
dc.contributor.school	School of Computer Science and Engineering	en_US
dc.description.degree	Bachelor of Engineering (Computer Science)	en_US
item.grantfulltext	restricted	-
item.fulltext	With Fulltext	-
Appears in Collections:	SCSE Student Reports (FYP/IA/PA/PI)

File	Description	Size	Format
jeremythia-fypreport.pdf Restricted Access		1.15 MB	Adobe PDF	View/Open

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