A heuristic for mining association rules in polynomial time

Authors:
E Yilmaz;E Triantaphyllou;J Chen;T.W Liao
Affiliations:
General Electric Card Services, Inc., A unit of General Electric Capital Corporation 1600 Summer Street, MS 1040-3029C, Stamford, CT 06927, U.S.A.;Department of Industrial and Manufacturing Systems Engineering Louisiana State University, 3128 CEBA Building, Baton Rouge, LA 70803, U.S.A.;Department of Computer Science, Louisiana State University 298 Coates Hall, Baton Rouge, LA 70803, U.S.A.;Department of Industrial and Manufacturing Systems Engineering Louisiana State University, 3128 CEBA Building, Baton Rouge, LA 70803, U.S.A.
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
2003

Citing 7
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Abstract

Mining association rules from databases has attracted great interest because of its potentially very practical applications. Given a database, the problem of interest is how to mine association rules (which could describe patterns of consumers' behaviors) in an efficient and effective way. The databases involved in today's business environments can be very large. Thus, fast and effective algorithms are needed to mine association rules out of large databases. Previous approaches may cause an exponential computing resource consumption. A combinatorial explosion occurs because existing approaches exhaustively mine all the rules. The proposed algorithm takes a previously developed approach, called the Randomized Algorithm 1 (or RA1), and adapts it to mine association rules out of a database in an efficient way. The original RA1 approach was primarily developed for inferring logical clauses (i.e., a Boolean function) from examples. Numerous computational results suggest that the new approach is very promising.