Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/32735
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dc.contributor.authorDashtipour, Kiaen_UK
dc.contributor.authorGogate, Mandaren_UK
dc.contributor.authorGelbukh, Alexanderen_UK
dc.contributor.authorHussain, Amiren_UK
dc.date.accessioned2021-06-22T00:29:56Z-
dc.date.available2021-06-22T00:29:56Z-
dc.identifier.urihttp://hdl.handle.net/1893/32735-
dc.description.abstractAssigning positive and negative polarity into Persian sentences is difficult task, there are different approaches has been proposed in various languages such as English. However, there is not any approach available to identify the final polarity of the Persian sentences. In this paper, the novel approach has been proposed to detect polarity for Persian sentences using PerSent lexicon (Persian lexicon). For this, we have proposed two different algorithms to detect polarity in the sentence and finally SVM, MLP and Na¨ıve Bayes classifier has been used to evaluate the performance of the proposed method. The SVM received better results in comparison with Na¨ıve Bayes and MLP.en_UK
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.relationDashtipour K, Gogate M, Gelbukh A & Hussain A (2021) Persian Sentence-level Sentiment Polarity Classification. In: TBC. ICOTEN 2021: International Congress of Advanced Technology and Engineering, Virtual, 04.07.2021-05.07.2021. Piscataway, NJ, USA: IEEE.en_UK
dc.rights© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_UK
dc.subjectSentiment Analysisen_UK
dc.subjectPersianen_UK
dc.subjectMachine Learningen_UK
dc.titlePersian Sentence-level Sentiment Polarity Classificationen_UK
dc.typeConference Paperen_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.contributor.funderEngineering and Physical Sciences Research Councilen_UK
dc.contributor.funderEPSRC Engineering and Physical Sciences Research Councilen_UK
dc.citation.btitleTBCen_UK
dc.citation.conferencedates2021-07-04 - 2021-07-05en_UK
dc.citation.conferencelocationVirtualen_UK
dc.citation.conferencenameICOTEN 2021: International Congress of Advanced Technology and Engineeringen_UK
dc.publisher.addressPiscataway, NJ, USAen_UK
dc.description.notesOutput Status: Forthcomingen_UK
dc.contributor.affiliationEdinburgh Napier Universityen_UK
dc.contributor.affiliationEdinburgh Napier Universityen_UK
dc.contributor.affiliationInstituto Politécnico Nacionalen_UK
dc.contributor.affiliationEdinburgh Napier Universityen_UK
dc.identifier.wtid1736916en_UK
dc.contributor.orcid0000-0001-8651-5117en_UK
dc.contributor.orcid0000-0003-1712-9014en_UK
dc.date.accepted2021-05-15en_UK
dcterms.dateAccepted2021-05-15en_UK
dc.date.filedepositdate2021-06-21en_UK
dc.relation.funderprojectTowards visually-driven speech enhancement for cognitively-inspired multi-modal hearing-aid devicesen_UK
dc.relation.funderrefEP/M026981/1en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeConference Paper/Proceeding/Abstracten_UK
rioxxterms.versionAMen_UK
local.rioxx.authorDashtipour, Kia|0000-0001-8651-5117en_UK
local.rioxx.authorGogate, Mandar|0000-0003-1712-9014en_UK
local.rioxx.authorGelbukh, Alexander|en_UK
local.rioxx.authorHussain, Amir|en_UK
local.rioxx.projectEP/M026981/1|Engineering and Physical Sciences Research Council|http://dx.doi.org/10.13039/501100000266en_UK
local.rioxx.freetoreaddate2021-06-21en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/all-rights-reserved|2021-06-21|en_UK
local.rioxx.filenamePersian_Polarity.pdfen_UK
local.rioxx.filecount1en_UK
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings

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