نمایش مختصر رکورد

dc.contributor.authorMirzaeian, Vahiden_US
dc.date.accessioned1399-07-08T17:22:15Zfa_IR
dc.date.accessioned2020-09-29T17:22:15Z
dc.date.available1399-07-08T17:22:15Zfa_IR
dc.date.available2020-09-29T17:22:15Z
dc.date.issued2019-11-01en_US
dc.date.issued1398-08-10fa_IR
dc.date.submitted2020-06-07en_US
dc.date.submitted1399-03-18fa_IR
dc.identifier.citationMirzaeian, Vahid. (2019). Sentimental Categorization of Persian News Headlines using Three Machine Learning Techniques Versus Human Categorization. Journal of Advances in Computer Research, 10(4), 1-10.en_US
dc.identifier.issn2345-606X
dc.identifier.issn2345-6078
dc.identifier.urihttp://jacr.iausari.ac.ir/article_675490.html
dc.identifier.urihttps://iranjournals.nlai.ir/handle/123456789/19389
dc.description.abstractThe aim of this paper is to elaborate on an attempt to classify Persian news headlines using machine learning techniques rather than human-based analysis. Three major techniques namely Naïve Bayes, Maximum Entropy and Support Vector Machine were introduced and applied to Persian news headlines. Results were compared with each other as well as the human analysis. It is concluded that these techniques outperform human analysis and one technique (Naïve Bayes) is superior to all the techniques mentioned. It can be concluded from this study that the inclusion of discourse analysis is necessary in order to attain better results since the whole is not necessarily the sum of the parts. It means that what you see in the headline does not necessarily reflect what is mentioned in the news itself. So it is recommended that in future studies, elements from discourse analysis be introduced into these algorithms so that better results can be achieved.en_US
dc.languageEnglish
dc.language.isoen_US
dc.publisherSari Branch, Islamic Azad Universityen_US
dc.relation.ispartofJournal of Advances in Computer Researchen_US
dc.subjectPersianen_US
dc.subjectheadlinesen_US
dc.subjectsentimenten_US
dc.subjectMachine Learningen_US
dc.subjectMaximum Entropyen_US
dc.subjectNaïve bayesen_US
dc.subjectH.3.8. Natural Language Processingen_US
dc.titleSentimental Categorization of Persian News Headlines using Three Machine Learning Techniques Versus Human Categorizationen_US
dc.typeTexten_US
dc.typeOriginal Manuscripten_US
dc.contributor.departmentELT Department, Alzahra University, Tehran, Iranen_US
dc.citation.volume10
dc.citation.issue4
dc.citation.spage1
dc.citation.epage10


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