Recommendation Framework for Products Using Optimization Algorithms

Abstract

The implementation of multi-criteria decision-making (MCDM) methodologies has been observed to be on the rise in the context of product recommendation decisions, which generally involve the consideration of multiple factors. The objective of this research is to showcase the execution of a new approach centered on PROMETHEE-I MCDM methodologies as the fundamental component of a Decision Support System for consumers. The proposed system recommends the most optimal choices from a provided range of alternatives. Despite its significance, relatively little research has been done on the topic of ranking products based on online product ratings and consumer preferences. The present study puts forth optimization techniques to rank products through the utilization of multi-attribute online ratings. Our study presents a new approach for recommending optimal alternatives through a mobile recommendation-ranking system-based (MCDM) method. The study utilized the PROMETHEE-I methodology to effectively rank the alternatives and address the optimal mobile recommendation issue. A case study illustrating the proposed methodology for selecting a mobile phone. This decision-making system may show to be the best long-term solution for e-commerce sites and websites due to its superior product comparison abilities and capacity to provide a recommendation to the user as a final ranking of alternatives.