A NEW SYSTEM FOR PRODUCT ASPECT RANKING IN DATA MINING

Abstract

Author(s): M.Guna Sekhar, J. Krishna

Ranking is a vital sequencing problem in many applications, like wise many information retrieval systems, language processors. Most retail Websites encourages consumers to write reviews to express their opinions on various aspects of the products. Here, an aspect, also called feature in literatures, and refers to a component or an attribute of a certain product. A sample review “The battery life of Nokia N95 is amazing." reveals positive opinion on the aspect “battery life" of product Nokia N95. Besides the retail Websites, many forum Websites also provide a platform for consumers to post reviews on millions of products. This article proposes a product aspect ranking framework, which automatically identifies the important aspects of products from online consumer reviews, aiming at improving the usability of the numerous reviews. The important product aspects are identified based on two observations: 1) the important aspects are usually commented on by a large number of consumers and 2) consumer opinions on the important aspects greatly influence their overall opinions on the product.