Designing a Deceptive Comment Detection Platform with a Rule-based Artificial Intelligent Architecture

Abstract

One of the most important factors in a purchasing decision nowadays is the evaluation of comments online. Businesses or individuals use deceptive comments to mislead people for the sake of economic gain and thus hurt the benefit of the customers and the welfare of society. In this research, we propose a rule-based artificial intelligence (AI) machine learning (ML) architecture for online review fraud detection. The proposed methodology features an AI and ML hybrid architecture, where ML refers to the common well-developed machine learning models, and the AI part features a rules-based controller that prioritizes and customizes the fraud detection rules based on human intelligence to improve the accuracy of the result and computational efficiency.