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- W1597962357 abstract "Frequent itemsets and association rules[Agrawal and Srikant 1994] are difficult to visualize. This is because that they are defined on elements of the power set of a set of items that reflect the many-to-many relationships among the items. With the absence of effective technique to visualize many-to-many relationships, association rules pose fundamental challenges to information visualization. We begin by defining a few terms: An itemset is a set of items. A transaction supports an itemset if the transaction contains all items in the itemset. Support of an itemset A, support(A), is defined as the percentage of transactions that support A. The support of a rule A → B is defined as support(A ∪ B). The confidence of the rule A → B is defined as support(A ∪ B)/support(A). An item group is a transitive closure of items in a set of frequent itemsets or association rules. Mining generalized association rules with item taxonomy was proposed in [Srikant and Agrawal 1995]. An example item taxonomy tree that organizes the items {a, b, c, d} is shown in Figure 1. A transaction T supports an item a if a ∈ T or a is an ancestor of some item in T under the item taxonomy. A transaction T supports an itemset A if T supports every item in A .A nancestor itemset A of A is obtained by replacing one or more items in A with their" @default.
- W1597962357 created "2016-06-24" @default.
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- W1597962357 date "2003-10-22" @default.
- W1597962357 modified "2023-09-26" @default.
- W1597962357 title "Visual Exploration of Association Rules" @default.
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- W1597962357 doi "https://doi.org/10.1109/vis.2003.10017" @default.
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