A Comparison of Machine Learning Algorithms in Opinion Polarity Classification of Customer Reviews (CROSBI ID 666461)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Žubrinić, Krunoslav ; Miličević, Mario ; Sjekavica, Tomo ; Obradović, Ines
engleski
A Comparison of Machine Learning Algorithms in Opinion Polarity Classification of Customer Reviews
In this paper we analyze reviews written by customers of an online shop, by employing opinion polarity classification on document level using five machine learning algorithms: Na¨ive Bayes, Support Vector Machine, Neural networks, C4.5 algorithm and classifier based on maximum entropy. We achieved the best results using Support Vector Machine algorithm (accuracy=0.845) and maximum entropy classifier (accuracy=0.84). Although those results are not as good as results that can be achieved in topic-based categorization, compared to similar researches in opinion polarity classification, they indicate a relatively good predictive performance of classical machine learning algorithms.
opinion polarity classification ; sentiment analysis ; natural language processing
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Podaci o prilogu
159-163.
2018.
objavljeno
Podaci o matičnoj publikaciji
International Journal of Computers, vol.3, 2018
Bojkovic, Z.
WSEAS Press ; IARAS
2367-8895
Podaci o skupu
18th International Conference on Applied Computer Science (ACS '18)
pozvano predavanje
26.09.2018-28.09.2018
Dubrovnik, Hrvatska