Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/835
DC FieldValueLanguage
dc.contributor.authorWang, Philips Fu Leeen_US
dc.contributor.authorXie, Haoran-
dc.contributor.otherYang, Q.-
dc.contributor.otherRao, Y.-
dc.contributor.otherWang, J.-
dc.contributor.otherChan, W. H.-
dc.date.accessioned2021-07-11T09:50:13Z-
dc.date.available2021-07-11T09:50:13Z-
dc.date.issued2019-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/835-
dc.description.abstractWith the rapid development of the Internet, an increasing number of users enjoy to shop online and express their reviews on the products and services. Analysis of these online reviews can not only help potential users make rational decisions when purchasing but also improves the quality of products and services. Hence, sentiment analysis for online reviews has become an important and meaningful research domain.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofIEEE Intelligent Systemsen_US
dc.titleSegment-level joint topic-sentiment model for online review analysisen_US
dc.typejournal articleen_US
dc.identifier.doi10.1109/MIS.2019.2899142-
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
dc.relation.issn1941-1294en_US
dc.description.volume34en_US
dc.description.issue1en_US
dc.description.startpage43en_US
dc.description.endpage50en_US
dc.cihe.affiliatedYes-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairetypejournal article-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
crisitem.author.deptSchool of Computing and Information Sciences-
Appears in Collections:CIS Publication
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