Abstract
Product recommendation in e-commerce is a widely applied technique which has been shown to bring benefits in both product sales and customer satisfaction. In this work we address a particular product recommendation setting — small-scale retail websites where the small amount of returning customers makes traditional user-centric personalization techniques inapplicable. We apply an item-centric product recommendation strategy which combines two well-known methods – association rules and text-based similarity – and demonstrate the effectiveness of the approach through two evaluation studies with real customer data.
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Acknowledgements
This research has been conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289.
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Kaminskas, M., Bridge, D., Foping, F., Roche, D. (2015). Product Recommendation for Small-Scale Retailers. In: Stuckenschmidt, H., Jannach, D. (eds) E-Commerce and Web Technologies. EC-Web 2015. Lecture Notes in Business Information Processing, vol 239. Springer, Cham. https://doi.org/10.1007/978-3-319-27729-5_2
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DOI: https://doi.org/10.1007/978-3-319-27729-5_2
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