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Lecture15 - Advances topics on association rules PART II
This document summarizes a lecture on advanced topics in association rule mining, including mining frequent patterns without candidate generation, multiple level association rules (AR), and quantitative AR. It discusses how concept hierarchies can be used to find associations between items at different levels of abstraction. Algorithms for mining generalized AR with taxonomies are presented, along with optimizations like pre-computing ancestors and pruning redundant rules. The importance of hierarchies for modeling real-world applications is highlighted.
