33 citations · 79 across the 35 of their papers we have counts for
Showing 2012 · cs.DBShow all
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cs.DB2012
A Comparative Study of Discretization Approaches for Granular Association Rule Mining
Xu He, Fan Min, William Zhu
Granular association rule mining is a new relational data mining approach to reveal patterns hidden in multiple tables. The current research of granular association rule mining con…
cs.DB2012★ 3 cited
Granular association rule mining through parametric rough sets for cold start recommendation
Fan Min, William Zhu
Granular association rules reveal patterns hide in many-to-many relationships which are common in relational databases. In recommender systems, these rules are appropriate for cold…
cs.DB2012★ 9 cited
Granular association rules on two universes with four measures
Fan Min
Relational association rules reveal patterns hide in multiple tables. Existing rules are usually evaluated through two measures, namely support and confidence. However, these two m…