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Mining market basket data using share measures and characterized itemsets
[chapter]
1998
Lecture Notes in Computer Science
A b s t r a c t . We propose the share-confidence framework for knowledge discovery from databases which addresses the problem of mining itemsets from market basket data. Our goal is two-fold: (1) to present new itemset measures which are practical and useful alternatives to the commonly used support measure; (2) to not only discover the buying patterns of customers, but also to discover customer profiles by partitioning customers into distinct classes. We present a new algorithm for
doi:10.1007/3-540-64383-4_14
fatcat:snuokc5p55daxgy25ihhsq2x7i