Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews

Table 2

Critical evaluation of aspects based classification methods.

Reference	Dataset; (hotels, restaurants)	Two-point scale	Five-point scale	Method	Type	Prediction	Results
Colhon et al., 2014 [21]	Review: 2521	Yes		Opinion terms counting method	Lexicon based	Compared with user reviews results	87%
Marrese-Taylor et al., 2014 [19]	Reviews: 200	Yes		Terms score method	Lexicon based	Compared with tourist experts results	90%
Pekar and Ou, 2008 [15]	Reviews: 268		Yes	Opinion terms intensity method	Lexicon based	Compared with judges results	78%
Marrese-Taylor et al., 2013 [18]	Reviews: 1435	Yes		Terms score method	Lexicon based	Compared with tourist experts results	83%
Muangon et al., 2014 [16]	Reviews: 2180	Yes		Terms score method	Lexicon based	Compared with online results	84%
Xianghua et al., 2013 [26]	Reviews: 300	Yes		Terms score method	Lexicon based	Compared with tourist experts results	75.89%
Wang et al., 2010 [23]	Reviews: 235,793		Yes	Support Vector Regression	Machine learning based	5-fold cross-validation	78%
Seki et al., 2009 [11]	Review: 1200	Yes		Naïve Bayes, SVM	Machine learning based	3-fold cross-validation	85%
Xueke et al., 2013 [27]	Reviews: 3214	Yes		Support Vector Machine	Machine learning based	7-fold cross-validation	83.9%
de Albornoz et al., 2011 [17]	Reviews: 1500	Yes		Logistic	Machine learning based	3-fold cross-validation	71.7%
Pontiki et al., 2014 [28]	Reviews: 300	Yes		Support Vector Machine	Machine learning based	3-fold cross-validation	80.15%
Pontiki et al., 2015 [29]	Reviews: 320	Yes		Maximum entropy	Machine learning based	3-fold cross-validation	78.69%
Proposed method	Reviews: 2000 (restaurants)	Yes		FURIA	Machine learning based	10-fold cross-validation	90.12%
Proposed method	Reviews: 4000 (hotels)	Yes		FLR	Machine learning based	10-fold cross-validation	86.02%