A heuristic for mining association rules in polynomial time
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. (C) 2003 Elsevier Science Ltd. All rights reserved.
heuristics association rules randomized algorithms boolean functions data mining algorithm analysis one clause at a time (ocat) approach