Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/163114
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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-
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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