Association Rule Mining on Streams
نویسندگان
چکیده
Let I = {i1, · · · , im} be a set of items. Let S be a stream of transactions in a sequential order, where each transaction is a subset of I. For an itemset X, which is a subset of I, a transaction T in S is said to contain the itemset X if X ⊆ T . The support of X is defined as the fraction of transactions in S that contain X. For a given support threshold s, X is frequent if the support of X is greater than or equal to s%, i.e., if at least s% transactions in S contain X. For a given confidence threshold c, an association rule X ⇒ Y holds if X ∪ Y is frequent and at least c% of transactions in S that contain X also contain Y . The problem of association rule mining on streams is to discover all association rules that hold in a stream of transactions.
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تاریخ انتشار 2009