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An efficient approach to mining indirect associations Qian Wan & Aijun An

Summary: An efficient approach to mining indirect associations
Qian Wan & Aijun An
Received: 14 February 2004 /Revised: 5 April 2005 /
Accepted: 27 May 2005
# Springer Science + Business Media, LCC 2006
Abstract Discovering association rules is one of the important tasks in data mining.
While most of the existing algorithms are developed for efficient mining of frequent
patterns, it has been noted recently that some of the infrequent patterns, such as
indirect associations, provide useful insight into the data. In this paper, we propose
an efficient algorithm, called HI-mine, based on a novel data structure, called HI-
struct, for mining the complete set of indirect associations between items. Our
experimental results show that HI-mine's performance is significantly better than
that of the previously developed algorithm for mining indirect associations on both
synthetic and real world data sets over practical ranges of support specifications.
Keywords Data mining . Association rule . Indirect association . Algorithm
1. Introduction
Since it was first introduced by Agarwal et al., in 1993, association rule mining has
been studied extensively by many researchers (Mannila et al., 1994; Park et al., 1995;
Savasere et al., 1995; Fayyad et al., 1996; Bayardo, 1998; Zaki et al., 1998; Agarwal
et al., 2000; Liu et al., 2002). As a result, many algorithms have been proposed to


Source: An, Aijun - Department of Computer Science, York University (Toronto)


Collections: Computer Technologies and Information Sciences