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Machine learning approach to recognize subject based sentiment values of reviews

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dc.contributor.author De Mel, NM
dc.contributor.author Hettiarachchi, HH
dc.contributor.author Madusanka, WPD
dc.contributor.author Malaka, GL
dc.contributor.author Perera, AS
dc.contributor.author Kohomban, U
dc.contributor.editor Jayasekara, AGBP
dc.contributor.editor Bandara, HMND
dc.contributor.editor Amarasinghe, YWR
dc.date.accessioned 2022-09-09T03:05:51Z
dc.date.available 2022-09-09T03:05:51Z
dc.date.issued 2016-04
dc.identifier.citation N. M. De Mel, H. H. Hettiarachchi, W. P. D. Madusanka, G. L. Malaka, A. S. Perera and U. Kohomban, "Machine learning approach to recognize subject based sentiment values of reviews," 2016 Moratuwa Engineering Research Conference (MERCon), 2016, pp. 6-11, doi: 10.1109/MERCon.2016.7480107. en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/18996
dc.description.abstract Due to the increase in the number of people participating online on reviewing travel related entities such as hotels, cities and attractions, there is a rich corpus of textual information available online. However, to make a decision on a certain entity, one has to read many such reviews manually, which is inconvenient. To make sense of the reviews, the essential first step is to understand the semantics that lie therein. This paper discusses a system that uses machine learning based classifiers to label the entities found in text into semantic concepts defined in an ontology. A subject classifier with a precision of 0.785 and a sentiment classifier with a correlation coefficient of 0.9423 was developed providing sufficient accuracy for subject categorization and sentiment evaluation in the proposed system. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.uri https://ieeexplore.ieee.org/document/7480107/ en_US
dc.subject Text classification en_US
dc.subject sentiment analysis en_US
dc.subject machine learning en_US
dc.subject feature engineering en_US
dc.title Machine learning approach to recognize subject based sentiment values of reviews en_US
dc.type Conference-Full-text en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Engineering Research Unit, University of Moratuwa en_US
dc.identifier.year 2016 en_US
dc.identifier.conference 2016 Moratuwa Engineering Research Conference (MERCon) en_US
dc.identifier.place Moratuwa, Sri Lanka en_US
dc.identifier.pgnos pp. 6-11 en_US
dc.identifier.proceeding Proceedings of 2016 Moratuwa Engineering Research Conference (MERCon) en_US
dc.identifier.email madhawi.11@cse.mrt.ac.lk en_US
dc.identifier.email hansi.11@cse.mrt.ac.lk en_US
dc.identifier.email danushka.11@cse.mrt.ac.lk en_US
dc.identifier.email glmalaka.11@cse.mrt.ac.lk en_US
dc.identifier.email shehang@cse.mrt.ac.lk en_US
dc.identifier.email upali@codegen.co.uk en_US
dc.identifier.doi 10.1109/MERCon.2016.7480107 en_US


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