A High-Performance Distributed Algorithm for Mining Association Rules

Abstract. We present a new distributed association rule mining (D-ARM) algorithm that demonstrates superlinear speed-up with the number of computing nodes. The algorithm is the first D-ARM algorithm to perform a single scan over the database. As such, its performance is unmatched by any previous algorithm. Scale-up experiments over standard synthetic benchmarks demonstrate stable run time regardless of the number of computers. Theoretical analysis reveals a tighter bound on error probability than the one shown in the corresponding sequential algorithm. As a result of this tighter bound, and by utilizing the combined memory of several computers, the algorithm generates far less candidates than comparable sequential algorithms – the same order of magnitude as the optimum.

• Type: Conference
• Year: 2003
• Where: ICDM
• Authors: Assaf Schuster, Ran Wolff, Dan Trock
• Keywords: Algorithms, Data Mining, ICDM 2003, Sequential Algorithms, first D-arm Algorithm