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References

  • Basic Concepts of Frequent Pattern Mining (Association Rules)
    • R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. SIGMOD'93.  
    • (Max-pattern) R. J. Bayardo. Efficiently mining long patterns from databases. SIGMOD'98.  
    • (Closed-pattern) N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal. Discovering frequent closed itemsets for association rules. ICDT'99.  
    • (Sequential pattern) R. Agrawal and R. Srikant. Mining sequential patterns. ICDE'95
  • Apriori and Its Improvements
    • R. Agrawal and R. Srikant. Fast algorithms for mining association rules. VLDB'94. 
    • H. Mannila, H. Toivonen, and A. I. Verkamo. Efficient algorithms for discovering association rules. KDD'94. 
    • A. Savasere, E. Omiecinski, and S. Navathe. An efficient algorithm for mining association rules in large databases. VLDB'95.
    • J. S. Park, M. S. Chen, and P. S. Yu. An effective hash-based algorithm for mining association rules. SIGMOD'95.
    • H. Toivonen. Sampling large databases for association rules. VLDB'96.
    • S. Brin, R. Motwani, J. D. Ullman, and S. Tsur. Dynamic itemset counting and implication rules for market basket analysis. SIGMOD'97.
    • S. Sarawagi, S. Thomas, and R. Agrawal. Integrating association rule mining with relational database systems: Alternatives and implications. SIGMOD'98.

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