Customer Reviews Mining using Machine Learning TechniqueDownload PDF
Nowadays large numbers of customers are choosing online shopping because of its convenience, reliability, and cost. As the number of products being sold online increases, it is becoming difficult for customers to make purchasing decisions based on only short product descriptions. For this reason customer’s product reviews are a crucial and very important part of ecommerce. Reviews are the opinion of the customer who bought product and other customers really take them into consideration before making a decision. As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. This makes it difficult for a potential customer to read them in order to make a decision on whether to buy the product. Customer reviews mining, particularly the text describing the features, comparisons and experiences of using a particular product provide a rich source of information to compare products and make purchasing decisions Product reviews are classify as either positive review or negative review. The purpose of this system is to classify reviews either positive review or negative review. To achieve these we used semantic analysis. It also includes pre-processing, POS tagging and feature extraction.
Keywords: POS tagger, Pre-processing, Features selection etc.