1997 · 373 citations · 10 references
ComputingComputer ScienceInformation SystemsData MiningKnowledge RepresentationData PreprocessingFrequent Pattern MiningKnowledge DiscoveryPattern EvaluationAssociation Rule EvaluationAssociation Rule LearningAssociation Rule MiningIncremental Frequent Pattern MiningRule Mining
A more general incremental updating technique is developed for maintaining the association rules discovered in a database in the cases including insertion, deletion, and modification of transactions in the database. A previously proposed algorithm FUP can only handle the maintenance problem in the case of insertion. The proposed algorithm FUP2 makes use of the previous mining result to cut down the cost of finding the new rules in an updated database. In the insertion only case, FUP2 is equivalent to FUP. In the deletion only case, FUP2 is a complementary algorithm of FUP which is very efficient when the deleted transactions is a small part of the database, which is the most applicable case. In the general case, FUP2 can efficiently update the discovered rules when new transactions are added to a transaction database, and obsolete transactions are removed from it. The proposed algorithm has been implemented and its performance is studied and compared with the best algorithms for mining association rules studied so far. The study shows that the new incremental algorithm is significantly faster than the traditional approach of mining the whole updated database.
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