Consider the transactions shown in Table 6.15, with an item taxonomy given in Figure 6.15 (Chapter 6)
(a) What are the main challenges of mining association rules with item taxonomy?
(b) Consider the approach where each transaction t is replaced by an extended transaction t_ that contains all the items in t as well as their respective ancestors. For example, the transaction t = { Chips, Cookies} will be replaced by t_ = {Chips, Cookies, Snack Food, Food}. Use this approach to derive all frequent itemsets (up to size 4) with support ≥ 70%.
(c) Consider an alternative approach where the frequent itemsets are generated one level at a time. Initially, all the frequent itemsets involving items at the highest level of the hierarchy are generated. Next, we use the frequent itemsets discovered at the higher level of the hierarchy to generate candidate itemsets involving items at the lower levels of the hierarchy. For example, we generate the candidate itemset {Chips, Diet Soda} only if {Snack Food, Soda} is frequent. Use this approach to derive all frequent itemsets (up to size 4) with support ≥ 70%.
