International Journal For Innovative Engineering and Management Research | 2021
BUYER RATING AND SENTIMENT ANALYSIS USING DISCRIMINATORY SUPPORT\nVECTOR MACHINE (SVM)
Abstract
This substantial issue is increasingly important in business and culture. It presents\nmany challenging research scenarios but guarantees a relevant insight for everybody\ninterested in view evaluation and social networking analysis. This paper s key aim is to detect\nsentiment polarity such as positive, negative, and emoji representation with customer\nfeedback on various products. Opinion mining from e-commerce sites has a significant part in\nmaking purchase decisions and founders to boost their product and marketing strategies. But,\nit becomes very difficult for the clients to understand and assess the product s actual view\nmanually. Because of this, we need an automated way. The majority of the researchers used\nmachine learning algorithms to do an automated representation of phrase embedding. Among\nthe popular techniques in machine learning has been used the support vector machine (SVM).\nThe weighted support vector machine (WSVM) is the improved version for the standard\nSVM to grow the outlier sensitivity issue. In this paper, the word2Vec version uses to extract\nthe attributes from customer reviews in WSVM based on opinion analysis of product reviews\nin E-commerce websites. The experiment result shows that the suggested WSVM can works\nbetter on the opinion classification job doing any version applied.