Opinion Analysis Model for Classification of Opinions for M Learning

Abstract

main objective of this research is to propose an Opinion Analysis Model for classification of opinions with the evolutionary approach and to improve the classification accuracy. The research presented three proposals to heed to various real-world problems. Some processes were posed, described, discussed and compared with existing classification algorithms. An improvement of classification accuracy is noticed when the data is preprocessed by KN preprocessing algorithm. Thus, the formed corpuses were applied in the existing classification algorithms which showed an increase in the accuracy rates. The enrichment of the classification algorithms with the neural network and genetic optimization brought a significant intervention in the classification accuracies. The research, for analyzing, took into account Mobile Learning (M- Learning) dataset from Android Market website. In order to assess the effectiveness of the proposed algorithms, the benchmark experiments are conducted with Internet Movie Database (IMDb) dataset comprising of movie reviews. KeywordsAnalysis Model (OAM), KN preprocessing algorithm, Classification Algorithms, Neural Network, Genetic Optimization, M-Learning, Internet Movie Database (IMDb) dataset.