Abstract
Narrowing down the computational space is a key factor in improving the efficiency of an association rule mining system. One approach to achieve this is to let the user guide the association rule mining process by enabling the user to specify the types of association rules that he/she might be interested in. Instead of computing all that can be computed, the system limits its association rule mining process to the discovery of only the association rules that may be of interest to the user, therefore, reducing the computational space and complexity. In this paper, we introduce a new approach for achieving this by using a new structure called lattice intension structure.
Highlights
Mining association rules is a complex, time-consuming process
This paper presents a new approach for association rule mining, where we introduce a new structure called lattice intension structure that enables the user to guide the association rule mining process
In (Alashqur, 2008), we introduced the concepts of itemset intension and association rule intension and distinguished them from itemset extension and association rule extension
Summary
Mining association rules is a complex, time-consuming process. One of the reasons behind this complexity can be attributed to the fact that the mining process aims at finding all possible association rules that satisfy minimum support and confidence values in a given database. This paper presents a new approach for association rule mining, where we introduce a new structure called lattice intension structure that enables the user to guide the association rule mining process. We describe how the lattice intension structure is used to enable the user to guide the data mining process. In (Alashqur, 2010), we introduced an algorithm that is based on SQL and that makes use of the itemset intension and extension structures for mining relational databases and discovering all frequent itemsets.
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