Recommendation system for localized products in vending machines

• Published in: Expert systems with applications Vol. 38; no. 8; pp. 9129 - 9138
• Main Authors: Lin, Feng-Cheng, Yu, Hsin-Wen, Hsu, Chih-Hao, Weng, Tzu-Chun
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-08-2011
• Subjects: Business; Classification; Customers; Expert systems; Feasibility; Genetic algorithm; Information services; Localized products recommendation system; Machine learning; Office buildings; Set cover problem; Vending machines; Vending machines; Localized products recommendation system; Genetic algorithm; Set cover problem; Machine learning
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2011.01.051

► This paper proposes a framework of localized product recommendation system for automatic vending machines applications. ► The goal is to offer suitable recommendations of localized products to customers in distinct locations. ► We develop a hybrid technique that combines a meta-heuristic approach, clustering technique, classification, and statistical method. ► An intelligent system is implemented to analyze product attributes and determine localized products based on the transaction data.
This paper proposes a framework of localized product recommendation system for automatic vending machines applications. The goal is to offer suitable recommendations of localized products to customers in distinct locations. We develop a hybrid technique that combines a meta-heuristic approach, clustering technique, classification, and statistical method. In the approach, an intelligent system is implemented to analyze product attributes and determine localized products based on the transaction data. To prove the feasibility and effectiveness of proposed approach, we implemented the system in several automatic vending machines owned by an information service company of Taiwan. Nine machines were selected and compared from two locations: living lab by Institute for Information Industry of Taiwan at Song-shan District and business office building at Nei-hu District in Taipei. The real life experiments showed that the profit of vending machine increases after applying our system.