Product Recommendation for e-Commerce System based on Ontology

Abstract

The sale and purchase of goods are now starting to move from being offline to online using the internet, or what is known as e-commerce. With the development of the internet and intelligent computing technology, e-commerce is increasingly being used. The products offered through e-commerce platforms is a matter that needs to be considered because it can influence the user's decision in buying a product. This study aims to build a product recommendation system on e-commerce platform according to user needs. There are several methods that can be used to produce recommendations, one of which is Collaborative Filtering. In this study, the Slope One algorithm is used where the input rating is given based on the domain ontology of the product. Domain ontology is used to represent relationships between products. Thus, the product recommendations are expected to be in accordance with the user's interest. So that product sales are right on target and users get products that suit their needs. This recommendation system will be implemented on e-commerce platforms and is expected to help users and sellers. Based on the case studies conducted, the results of recommendations provided with the ontology approach not only provide recommendations for specific products, but also provide recommendations on categories that may be of interest to the users. Thus, the recommendations will be more varied and are expected to be more in line with user interests.