An expert system for extracting knowledge from customers' reviews: The case of Amazon.com, Inc. (30th October 2017)

• Record Type: Journal Article
• Authors: Castelli, Mauro; Manzoni, Luca; Vanneschi, Leonardo; Popovič, Aleš
• Is Part Of: Expert systems with applications. Volume 84(2017)
• Page Start: 117
• Page End: 126
• Publication Date: 2017-10-30
• Subjects: Genetic programming -- Semantics -- E-commerce -- Customers' feedback; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2017.05.008
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: A system for the prediction of the success of products available on Amazon. Prediction based on the feedbacks of the users. A system that outperforms existing state of the art techniques. A system based on the concept of semantics. A system able to process a large amount of data in an acceptable amount of time. Abstract: E-commerce has proliferated in the daily activities of end-consumers and firms alike. For firms, consumer satisfaction is an important indicator of e-commerce success. Today, consumers' reviews and feedback are increasingly shaping consumer intentions regarding new purchases and repeated purchases, while helping to attract new customers. In our work, we use an expert system to predict the sentiment of a product considering a subset of available customers' reviews.