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Association rule mining is a data mining technique used to discover interesting relationships, patterns, and associations among items in large transactional databases. It is widely applied in market basket analysis, recommendation systems, inventory management, healthcare, and web usage mining. The objective is to identify itemsets that frequently occur together and generate rules that help predict the occurrence of one item based on the presence of another. Consider the following transaction dataset: | Transaction ID | Items Purchased | | -------------- | ------------------------- | | T1 | Bread, Milk | | T2 | Bread, Diaper, Beer, Eggs | | T3 | Milk, Diaper, Beer, Cola | | T4 | Bread, Milk, Diaper, Beer | | T5 _____ _________ __________ ____ ______ __________ ______ _______.
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