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Improving Co-Cluster Quality with Application to Product Recommendations
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management - CIKM '14
Businesses store an ever increasing amount of historical customer sales data. Given the availability of such information, it is advantageous to analyze past sales, both for revealing dominant buying patterns, and for providing more targeted recommendations to clients. In this context, co-clustering has proved to be an important datamodeling primitive for revealing latent connections between two sets of entities, such as customers and products. In this work, we introduce a new algorithm fordoi:10.1145/2661829.2661980 dblp:conf/cikm/VlachosFMKV14 fatcat:rqsuynf5drg3namiujtw4if2eu