Using association rules for product assortment decisions: a case study
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
An MDP-Based Recommender System
The Journal of Machine Learning Research
Improving the prediction accuracy of recommendation algorithms: Approaches anchored on human factors
Interacting with Computers
A probabilistic model for item-based recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
A case study on the effectiveness of recommendations in the mobile internet
Proceedings of the third ACM conference on Recommender systems
Engineering Applications of Artificial Intelligence
The impact of recommender systems on item-, user-, and rating-diversity
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
Accuracy improvements for multi-criteria recommender systems
Proceedings of the 13th ACM Conference on Electronic Commerce
Case study on the business value impact of personalized recommendations on a large online retailer
Proceedings of the sixth ACM conference on Recommender systems
Stability of Recommendation Algorithms
ACM Transactions on Information Systems (TOIS)
Top-N recommendation through belief propagation
Proceedings of the 21st ACM international conference on Information and knowledge management
How should I explain? A comparison of different explanation types for recommender systems
International Journal of Human-Computer Studies
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Recommender systems have recently grown in popularity both in e-commerce and in research. However, there is little, if any, direct evidence in the literature of the value of recommender systems to e-Businesses, especially relating to consumer packaged goods (CPG) sold in a supermarket setting. We have been working in collaboration with LeShop (www.LeShop.ch), to gather real evidence of the added business value of a personalised recommender system. In this paper, we present our initial evaluation of the performance of our model-based personalised recommender systems over the 21-month period from May 2006 to January 2008, with particular focus on the added-value to the business. Our analysis covers shopper penetration, as well as the direct and indirect extra revenue generated by our recommender systems. One of the key lessons we have learnt during this case study is that the effect of a recommender system extends far beyond the direct extra revenue generated from the purchase of recommended items. The importance of maintaining updated model files was also found to be key to maintaining the performance of such model-based systems.