Feature Extraction of Customer Reviews Using Frequent Pattern Mining Algorithm

Selling the product through the Web has become more popular because of online shopping. As e-commerce is becoming more and more familiar, the number of customer reviews that a product receives grows quickly. For a accepted product, the amount of reviews can be in hundreds or level thousands. This makes it difficult for a potential customer to read them in order to make a decision to buy the product. The main objective of this work is to discuss about developing an information extraction system which mines customer reviews in order to build a model to extract important product feature and their evaluation by reviewers. In this paper, we present a frequent pattern mining algorithm to mine a number of reviews and extract product features. Our new result indicates the algorithm outperforms the old pattern mining techniques used by previous researchers.