ADAPTIVE-FP: AN EFFICIENT AND EFFECTIVE METHOD FOR MULTI-LEVEL MULTI-DIMENSIONAL FREQUENT PATTERN MINING

iii Acknowledgment iv Dedication v List of Tables viii List of Figures ix

[1]  Jinyan Li,et al.  Efficient mining of emerging patterns: discovering trends and differences , 1999, KDD '99.

[2]  Rajeev Motwani,et al.  Beyond market baskets: generalizing association rules to correlations , 1997, SIGMOD '97.

[3]  Jiawei Han,et al.  Discovery of Multiple-Level Association Rules from Large Databases , 1995, VLDB.

[4]  HanJiawei,et al.  Exploratory mining and pruning optimizations of constrained associations rules , 1998 .

[5]  Ke Wang,et al.  Building Hierarchical Classifiers Using Class Proximity , 1999, VLDB.

[6]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[7]  Wynne Hsu,et al.  Integrating Classification and Association Rule Mining , 1998, KDD.

[8]  Hannu Toivonen,et al.  Sampling Large Databases for Association Rules , 1996, VLDB.

[9]  Ke Wang,et al.  Mining Frequent Itemsets Using Support Constraints , 2000, VLDB.

[10]  Dimitris Meretakis,et al.  Extending naïve Bayes classifiers using long itemsets , 1999, KDD '99.

[11]  Nicolas Pasquier,et al.  Discovering Frequent Closed Itemsets for Association Rules , 1999, ICDT.

[12]  Jian Pei,et al.  DNA-miner: a system prototype for mining DNA sequences , 2001, SIGMOD '01.

[13]  Jian Pei,et al.  Mining frequent patterns without candidate generation , 2000, SIGMOD '00.

[14]  Qiming Chen,et al.  PrefixSpan,: mining sequential patterns efficiently by prefix-projected pattern growth , 2001, Proceedings 17th International Conference on Data Engineering.

[15]  Renée J. Miller,et al.  Association rules over interval data , 1997, SIGMOD '97.

[16]  Salvatore J. Stolfo,et al.  Mining Audit Data to Build Intrusion Detection Models , 1998, KDD.

[17]  Heikki Mannila,et al.  Finding interesting rules from large sets of discovered association rules , 1994, CIKM '94.

[18]  Edith Cohen,et al.  Finding Interesting Associations without Support Pruning , 2001, IEEE Trans. Knowl. Data Eng..

[19]  Ramakrishnan Srikant,et al.  Mining quantitative association rules in large relational tables , 1996, SIGMOD '96.

[20]  Wynne Hsu,et al.  Mining association rules with multiple minimum supports , 1999, KDD '99.

[21]  Jian Pei,et al.  Towards data mining benchmarking: a test bed for performance study of frequent pattern mining , 2000, SIGMOD '00.

[22]  Jiawei Han,et al.  Metarule-Guided Mining of Multi-Dimensional Association Rules Using Data Cubes , 1997, KDD.

[23]  Ramakrishnan Srikant,et al.  Mining Association Rules with Item Constraints , 1997, KDD.

[24]  Ramakrishnan Srikant,et al.  Mining sequential patterns , 1995, Proceedings of the Eleventh International Conference on Data Engineering.

[25]  Charu C. Aggarwal,et al.  A Tree Projection Algorithm for Generation of Frequent Item Sets , 2001, J. Parallel Distributed Comput..

[26]  Shamkant B. Navathe,et al.  An Efficient Algorithm for Mining Association Rules in Large Databases , 1995, VLDB.

[27]  Roberto J. Bayardo,et al.  Efficiently mining long patterns from databases , 1998, SIGMOD '98.

[28]  Ramakrishnan Srikant,et al.  Mining generalized association rules , 1995, Future Gener. Comput. Syst..

[29]  Heikki Mannila,et al.  Efficient Algorithms for Discovering Association Rules , 1994, KDD Workshop.

[30]  Umeshwar Dayal,et al.  FreeSpan: frequent pattern-projected sequential pattern mining , 2000, KDD '00.

[31]  Jiawei Han,et al.  Efficient mining of partial periodic patterns in time series database , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[32]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[33]  Ramakrishnan Srikant,et al.  Mining Sequential Patterns: Generalizations and Performance Improvements , 1996, EDBT.

[34]  Zvi M. Kedem,et al.  Pincer-Search: A New Algorithm for Discovering the Maximum Frequent Set , 1998, EDBT.

[35]  Philip S. Yu,et al.  Data Mining: An Overview from a Database Perspective , 1996, IEEE Trans. Knowl. Data Eng..

[36]  Jennifer Widom,et al.  Clustering association rules , 1997, Proceedings 13th International Conference on Data Engineering.

[37]  Rakesh Agarwal,et al.  Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.

[38]  Rajeev Motwani,et al.  Dynamic itemset counting and implication rules for market basket data , 1997, SIGMOD '97.

[39]  Jian Pei,et al.  CLOSET: An Efficient Algorithm for Mining Frequent Closed Itemsets , 2000, ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery.