Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/163114
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGoh, Nicholasen_US
dc.date.accessioned2022-11-24T01:44:50Z-
dc.date.available2022-11-24T01:44:50Z-
dc.date.issued2022-
dc.identifier.citationGoh, N. (2022). News article named entity recognition and analytics. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/163114en_US
dc.identifier.urihttps://hdl.handle.net/10356/163114-
dc.description.abstractText analytics have been essential in today’s data driven world. Search engines such as Elasticsearch are widely used to retrieve documents based on user queries that would otherwise be impossible for a human to manually sift through and retrieve. NER models classify important phrases in a paragraph of text. Feature vectors can be extracted from NER models to compare similarity between different texts. However, there has been little work where these 3 tools have been used together.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titleNews article named entity recognition and analyticsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorSun Aixinen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Science in Data Science and Artificial Intelligenceen_US
dc.contributor.supervisoremailAXSun@ntu.edu.sgen_US
item.grantfulltextrestricted-
item.fulltextWith Fulltext-
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
Files in This Item:
File Description SizeFormat 
FYP.pdf
  Restricted Access
1.61 MBAdobe PDFView/Open

Page view(s)

24
Updated on Jan 29, 2023

Download(s)

4
Updated on Jan 29, 2023

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.