DISCOVERING CONFUSING FREQUENT ITEMSETS - Huỳnh Thành Lộc (Tạp chí Khoa học Đại học Đà Lạt)
Frequent itemset mining is one of the most important research areas in the field of association rule mining. Exploiting frequent itemsets at different abstraction levels of data will yield valuable knowledge. However, some Confusing Frequent Itemsets (CFIs) could be included in the mined set. These CFIs represent contrasting knowledge with their low-level descendants. Experts need to analyze CFIs from traditional frequent itemsets to make more accurate recommendations. In this paper, we presented a definition of a CFI, CFI’s interestingness measure and how to apply existing frequent itemset mining techniques to discover CFIs from data by exploiting a taxonomy.