Abstract
Given a large collection of transactions containing items, a basic common association rules problem is the huge size of the extracted rule set. Pruning uninteresting and redundant association rules is a promising approach to solve this problem. In this paper, we propose a Condensed Representation for Positive and Negative Association Rules representing non-redundant rules for both exact and approximate association rules based on the sets of frequent generator itemsets, frequent closed itemsets, maximal frequent itemsets, and minimal infrequent itemsets in database B. Experiments on dense (highly-correlated) databases show a significant reduction of the size of extracted association rule set in database B.
Highlights
Introduction and MotivationsPositive and negative association rules (PNAR) mining have been studied extensively in Data mining problem
This rule can indicate the positive relations between different items, is called positive association rule (PAR) in database B. the association rule at other three forms X → Y, X → Y and X → Y, which can indicate the negative relations between items in database B, are called negative association rules (NAR) in database B
We propose a Condensed Representation representing non-redundant positive and negative association rules based on generator itemsets, closed itemsets, maximal
Summary
Positive and negative association rules (PNAR) mining have been studied extensively in Data mining problem. We propose a Condensed Representation representing non-redundant positive and negative association rules based on generator itemsets, closed itemsets, maximal. 2) We introduce a formal definition for uninteresting association rules (UAR), propose an efficient strategy for pruning UAR using MGK measure [7]. 4) We propose three new efficient bases based on MGK measure : Concise Basis for Positive Approximate Rules (CBA), Concise Basis for Negative Exact Rules (CBE−), and Concise Basis for Negative Approximate Rules (CBA−) We prove that these concise bases are a lossless representation of non-redundant rules since all valid rules can be derived from these (cf Theorems 2, 3, 4 and 5).
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