Hybrid Multi-Criteria Decision Making Approach for Product Ranking Using Customers Reviews
Rakesh Kumar, Aditi Sharan
Journal of Data Processing, Vol. 8, No. 1, 2018.
DOI: 
Link: http://www.dline.info/jdp/fulltext/v8n1/jdpv8n1_1.pdf
Abstract:
Consumerâ€˜s reviews provided with the product descriptions play a great role in the popularity of E-commerce Web sites. However, there are various products, which have thousands of user generated reviews. Mining this enormous online reviews and tuning these abundant individual consumers view into collective consumerâ€˜s choice became a challenging task. These collective reviews aid in product improvement processes, ranking of various  products, and many other such operations. This paper proposes a hybrid Multi-Criteria Decision Making (MCDM) approach for product ranking. The proposed approach
consists of two steps: 1) Buckley Analytic Hierarchy Process (AHP) to find out the relative weights of evaluation criteria and, 2) Ranked Voting Method (RVM) to determine rank of cell phone alternatives. Experiment is carried on real dataset collected from Amazon web sites. We have also compared our AHP-RVM approach with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method.