Product recommendations for cross-selling in electronic business

Authors:
Bharat Bhasker;Ho-Hyun Park;Jaehwa Park;Hyong-Soon Kim
Affiliations:
Indian Institute of Management, Lucknow, India;School of Electrical and Electronics Engineering, Chung-Ang University, Korea;School of Electrical and Electronics Engineering, Chung-Ang University, Korea;Next Generation Internet Team, National Computerization Agency, Korea
Venue:
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Year:
2006

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Abstract

A system applicable in electronic commerce environments that combines the strengths of both collaborative filtering and data mining for providing better recommendations is presented. It captures the item-to-item relationship through association rule mining and then uses purchase behaviour of collaborative users for generating the recommendations. It was implemented and evaluated on a set of real datasets. Our methodology results in improved quality of recommendations measured in terms of recall and coverage metrics.