Title :
Product recommendation system for small online retailers using association rules mining
Author :
Junnan Chen ; Miller, Colin ; Dagher, Gaby G.
Abstract :
Recommendation systems in e-commerce have become essential tools to help businesses increase their sales. In this paper, we detail the design of a product recommendation system for small online retailers. Our system is specifically designed to address the needs of retailers with small data pools and limited processing power, and is tested for accuracy, efficiency, and scalability on real life data from a small online retailer.
Keywords :
Internet; data mining; electronic commerce; recommender systems; retailing; association rules mining; data pools; e-commerce; product recommendation system design; small online retailers; Algorithm design and analysis; Association rules; Companies; Databases; Libraries; Data Mining; Database Management; E-commerce; Performance;
Conference_Titel :
Innovative Design and Manufacturing (ICIDM), Proceedings of the 2014 International Conference on
Conference_Location :
Montreal, QC
Print_ISBN :
978-1-4799-6269-3
DOI :
10.1109/IDAM.2014.6912673
