Predicting Supervise Machine Learning Performances for Sentiment Analysis Using Contextual-Based Approaches
| dc.contributor.author | Abdul Aziz, Azwa | |
| dc.contributor.author | Starkey, Andrew | |
| dc.contributor.institution | University of Aberdeen.Engineering | en |
| dc.contributor.institution | University of Aberdeen.Engineering | en |
| dc.contributor.institution | University of Aberdeen.Energy | en |
| dc.contributor.institution | University of Aberdeen.Centre for Applied Dynamics Research (CADR) | en |
| dc.date.accessioned | 2020-02-04T00:06:11Z | |
| dc.date.available | 2020-02-04T00:06:11Z | |
| dc.date.issued | 2020-01-28 | |
| dc.description.status | Peer reviewed | en |
| dc.format.extent | 12 | |
| dc.format.extent | 7595295 | |
| dc.identifier | 156506080 | |
| dc.identifier | 97c87b2d-1890-4987-a899-edca9cb54bca | |
| dc.identifier | 85079777399 | |
| dc.identifier.citation | Abdul Aziz, A & Starkey, A 2020, 'Predicting Supervise Machine Learning Performances for Sentiment Analysis Using Contextual-Based Approaches', IEEE Access, vol. 8, pp. 17722-17733. https://doi.org/10.1109/ACCESS.2019.2958702 | en |
| dc.identifier.doi | 10.1109/ACCESS.2019.2958702 | |
| dc.identifier.issn | 2169-3536 | |
| dc.identifier.uri | https://hdl.handle.net/2164/13652 | |
| dc.identifier.url | http://www.scopus.com/inward/record.url?scp=85079777399&partnerID=8YFLogxK | en |
| dc.identifier.vol | 8 | en |
| dc.language.iso | eng | |
| dc.relation.ispartof | IEEE Access | en |
| dc.subject | Text analytics | en |
| dc.subject | sentiment analysis | en |
| dc.subject | contextual analysis | en |
| dc.subject | supervised machine learning | en |
| dc.subject | TA Engineering (General). Civil engineering (General) | en |
| dc.subject | General Engineering | en |
| dc.subject | General Materials Science | en |
| dc.subject | General Computer Science | en |
| dc.subject.lcc | TA | en |
| dc.title | Predicting Supervise Machine Learning Performances for Sentiment Analysis Using Contextual-Based Approaches | en |
| dc.type | Journal article | en |
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