Ranking Analysis for Online Customer Reviews of Products Using Opinion Mining with Clustering
S. K. Lakshmanaprabu, K. Shankar, Deepak Kumar Gupta, Ashish K. Khanna, Joel J. P. C. Rodrigues, Plácido Rogério Pinheiro, Victor Hugo C. de Albuquerque · Complexity · 2018
Sites for web‐based shopping are winding up increasingly famous these days. Organizations are anxious to think about their client purchasing conduct to build their item deal. Internet shopping is a method for powerful exchange among cash and merchandise which is finished by end clients without investing a huge energy spam. The goal of this paper is to dissect the high‐recommendation web‐based business sites with the help of a collection strategy and a swarm‐based improvement system. At first, the client surveys of the items from web‐based business locales with a few features were gathered and, afterward, a fuzzy c‐means (FCM) grouping strategy to group the features for a less demanding procedure was utilized. Also, the novelty of this work—the Dragonfly Algorithm (DA)—recognizes ideal features of the items in sites, and an advanced ideal feature‐based positioning procedure will be directed to discover, at long last, which web‐based business webpage is best and easy to understand. From the execution, the outcomes demonstrate the greatest exactness rate, that is, 94.56% compared with existing methods.