Smartphone Like Dislike Classification Using MP-Neuron and Perceptron Models

Abstract

With the day-by-day increasing revolutionary advancements in smartphone technologies, the users tend to buy smartphones more often than ever before. From a vast variety of brands and models to choose from, the users also check for opinions and ratings from e-commerce websites before buying one. The primary aim of smartphone like dislike classifier is to classify a smartphone with given specifications into like or dislike. It is an automated approach to identify the people's opinion on smartphones with given specifications of the phone. Real Dataset is obtained from Kaggle. The Smartphone Like Dislike Classifier is developed using the MP-Neuron and Perceptron model-based approaches. It helps manufacturers as well as users to know whether the people would like or dislike the phone even before the launch of a smartphone. We show extensive experimental results demonstrating the efficacy of our approach. Experiment results prove meaningful and useful, not only for end users, but also for the smartphone industries.