Abstract

Abstract: In recent years, use of onlineshopping has increased rapidly. Majority of the public chooses online shoppingoption than traditional era methods which also ensures saving energy and money.People preferably share their attitude, opinion about the products or services,feature and quality based on their experiences on web. But for analysis ofproduct or service it is tough for customers to read all the reviews of aparticular product available on the internet. Due to preceded issue, there is aneed to design methods which can distinguish positive and negative feedbacks ofthe users to assist customers for acquiring their favorite product promptly.Consequently, we have proposed Review Based Linguistic Classification forProduct Ranking (RLCPR) framework to rank the products effectively by usingopinion mining techniques. RLCPR contribute users for specifying productfeatures to get back the ranking result of all matched goods. The proposeddesign also overcomes the short forms of the words used by customers for reviewprocess in present scenario. This process considerably allows parser toidentify and tag such words in order to improve the ranking results.

General Terms - Opinion mining

Keywords– Reviews,product ranking, opinion mining, POS, XML documents