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Parametric Rough Sets with Application to Granular Association Rule Mining
2013
Mathematical Problems in Engineering
Granular association rules reveal patterns hidden in many-to-many relationships which are common in relational databases. In recommender systems, these rules are appropriate for cold-start recommendation, where a customer or a product has just entered the system. An example of such rules might be "40% men like at least 30% kinds of alcohol; 45% customers are men and 6% products are alcohol." Mining such rules is a challenging problem due to pattern explosion. In this paper, we build a new type
doi:10.1155/2013/461363
fatcat:4ga4cvkw7zcehd4laarfvrc4b4