Intelligent Aspect based Model for Efficient Sentiment Analysis of User Reviews
M. Deva Priya, R. Rithika · CVR Journal of Science & Technology · 2021
Mining online reviews to extract opinion targets and words are substantial tasks in fine-grained opinion mining.The main aim is to mine sensible multi-grain aspects and opinion words from unlabeled reviews.In this paper, Combined Aspect based Sentiment Model (CASM) is propounded to cooperatively mine multi-grain features and opinions.CASM deals with aspects, opinions, sentiment polarity and granularity concurrently.Support Vector Machine-Radial Basis Function kernel (SVM-RBF) classifier is applied to improve CASM by splitting aspects and opinion words.CASM-SVM-RBF deals with two different kinds of aspects and opinions: general and particular aspects, overall opinions and aspect-precise opinions.Candidates with improved confidence are mined as opinion targets or words.The performance is analyzed in terms of Accuracy, Precision, Recall and F-Score for KNN, BPNN, NBC and ME classifiers.