A PERCEPTION CLASSIFICATION USING HYBRID FEATURE EXTRACTION
C. Suganthi · INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH · 2022
The estimation of product quality is more signicant during the purchasing of online products. Therefore, many opinion mining and sentiment classication methods were introduced to purchase the best products through online shopping. But, these classication methods haven't attained the effective product classication with best reviews and ratings. Several popular classication algorithms estimated along with three ltering Methods. Presented a hybrid technique to extract the product features. In this method, association rules and point-wise mutual information is combine. Large amount of features of products, not only to increase the time of computation but also to increase accuracy of classication. Optimize the amount of marketing funds spent on each customer, and just making a binary decision on whether to market to him. General Purpose Emotion Lexicons (GPELs) that associate with emotion categories remain a valuable resource for emotion analysis. Proposed a hybrid feature extraction method PCA (Principle Component Analysis) using lexicon-based method to classify and separate the products from the large set of different products depending on their features, best product ratings and positive reviews.