Frequent Pattern Mining Algorithms: A Survey
暂无分享,去创建一个
Charu C. Aggarwal | Mohammad Al Hasan | Mansurul Bhuiyan | C. Aggarwal | M. Hasan | Mansurul Bhuiyan
[1] Devavrat Shah,et al. Turbo-charging vertical mining of large databases , 2000, SIGMOD 2000.
[2] Christian Borgelt,et al. Induction of Association Rules: Apriori Implementation , 2002, COMPSTAT.
[3] Fumito Ito,et al. Current Status and Future Directions , 2013 .
[4] Anthony K. H. Tung,et al. Carpenter: finding closed patterns in long biological datasets , 2003, KDD '03.
[5] Salvatore Orlando,et al. Fast and memory efficient mining of frequent closed itemsets , 2006, IEEE Transactions on Knowledge and Data Engineering.
[6] Salvatore Orlando,et al. DCI Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets , 2004, FIMI.
[7] Hongyan Liu,et al. Mining Interesting Patterns from Very High Dimensional Data: A Top-Down Row Enumeration Approach , 2006, SDM.
[8] Shamkant B. Navathe,et al. An Efficient Algorithm for Mining Association Rules in Large Databases , 1995, VLDB.
[9] Jiawei Han,et al. TFP: an efficient algorithm for mining top-k frequent closed itemsets , 2005, IEEE Transactions on Knowledge and Data Engineering.
[10] Ramakrishnan Srikant,et al. Fast algorithms for mining association rules and sequential patterns , 1996 .
[11] Johannes Gehrke,et al. MAFIA: a maximal frequent itemset algorithm for transactional databases , 2001, Proceedings 17th International Conference on Data Engineering.
[12] Tomasz Imielinski,et al. Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.
[13] Salvatore Orlando,et al. Enhancing the Apriori Algorithm for Frequent Set Counting , 2001, DaWaK.
[14] Osmar R. Zaïane,et al. COFI-tree Mining: A New Approach to Pattern Growth with Reduced Candidacy Generation , 2003, FIMI.
[15] 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.
[16] Mohammed J. Zaki,et al. Fast vertical mining using diffsets , 2003, KDD '03.
[17] Raj P. Gopalan,et al. CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure , 2004, FIMI.
[18] Won Suk Lee,et al. Finding recent frequent itemsets adaptively over online data streams , 2003, KDD '03.
[19] Gerd Stumme,et al. Mining frequent patterns with counting inference , 2000, SKDD.
[20] Charu C. Aggarwal,et al. A Tree Projection Algorithm for Generation of Frequent Item Sets , 2001, J. Parallel Distributed Comput..
[21] Rajeev Motwani,et al. Beyond market baskets: generalizing association rules to correlations , 1997, SIGMOD '97.
[22] Fabrizio Silvestri,et al. Adaptive and resource-aware mining of frequent sets , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..
[23] Régis Gras,et al. Using information-theoretic measures to assess association rule interestingness , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).
[24] Robin Milner,et al. On Observing Nondeterminism and Concurrency , 1980, ICALP.
[25] Nicolas Pasquier,et al. Mining Bases for Association Rules Using Closed Sets , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).
[26] Defu Zhang,et al. A New Algorithm for Frequent Itemsets Mining Based on Apriori and FP-Tree , 2009, 2009 WRI Global Congress on Intelligent Systems.
[27] Mohammed J. Zaki,et al. GenMax: An Efficient Algorithm for Mining Maximal Frequent Itemsets , 2005, Data Mining and Knowledge Discovery.
[28] Anthony K. H. Tung,et al. Mining top-K covering rule groups for gene expression data , 2005, SIGMOD '05.
[29] Rajeev Motwani,et al. Dynamic itemset counting and implication rules for market basket data , 1997, SIGMOD '97.
[30] Rajeev Motwani,et al. Approximate Frequency Counts over Data Streams , 2012, VLDB.
[31] Ramesh C Agarwal,et al. Depth first generation of long patterns , 2000, KDD '00.
[32] Anthony K. H. Tung,et al. FARMER: finding interesting rule groups in microarray datasets , 2004, SIGMOD '04.
[33] Moses Charikar,et al. Finding frequent items in data streams , 2004, Theor. Comput. Sci..
[34] Hannu Toivonen,et al. Sampling Large Databases for Association Rules , 1996, VLDB.
[35] Nicolas Pasquier,et al. Discovering Frequent Closed Itemsets for Association Rules , 1999, ICDT.
[36] Mohammed J. Zaki. Scalable Algorithms for Association Mining , 2000, IEEE Trans. Knowl. Data Eng..
[37] Toon Calders,et al. Mining All Non-derivable Frequent Itemsets , 2002, PKDD.
[38] Hongjun Lu,et al. H-mine: hyper-structure mining of frequent patterns in large databases , 2001, Proceedings 2001 IEEE International Conference on Data Mining.
[39] Bart Goethals,et al. A tight upper bound on the number of candidate patterns , 2001, Proceedings 2001 IEEE International Conference on Data Mining.
[40] Gösta Grahne,et al. Efficiently Using Prefix-trees in Mining Frequent Itemsets , 2003, FIMI.
[41] Philip S. Yu,et al. A new framework for itemset generation , 1998, PODS '98.
[42] Ruoming Jin,et al. An algorithm for in-core frequent itemset mining on streaming data , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).
[43] Anthony K. H. Tung,et al. COBBLER: combining column and row enumeration for closed pattern discovery , 2004, Proceedings. 16th International Conference on Scientific and Statistical Database Management, 2004..
[44] Christian Hidber,et al. Association Rule Mining , 2017 .
[45] Heikki Mannila,et al. Efficient Algorithms for Discovering Association Rules , 1994, KDD Workshop.
[46] Anton Dries,et al. Dominance Programming for Itemset Mining , 2013, 2013 IEEE 13th International Conference on Data Mining.
[47] Mohammed J. Zaki,et al. CHARM: An Efficient Algorithm for Closed Association Rule Mining , 2007 .
[48] Gösta Grahne,et al. Fast algorithms for frequent itemset mining using FP-trees , 2005, IEEE Transactions on Knowledge and Data Engineering.
[49] Srinivasan Parthasarathy,et al. New Algorithms for Fast Discovery of Association Rules , 1997, KDD.
[50] Philip S. Yu,et al. An effective hash-based algorithm for mining association rules , 1995, SIGMOD '95.
[51] Nicolas Pasquier,et al. Efficient Mining of Association Rules Using Closed Itemset Lattices , 1999, Inf. Syst..
[52] Bart Goethals,et al. Survey on Frequent Pattern Mining , 2003 .
[53] Raj P. Gopalan,et al. CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth , 2003, ADC.
[54] Heikki Mannila,et al. Fast Discovery of Association Rules , 1996, Advances in Knowledge Discovery and Data Mining.
[55] Ramakrishnan Srikant,et al. Fast algorithms for mining association rules , 1998, VLDB 1998.
[56] Valerie Guralnik,et al. Parallel tree-projection-based sequence mining algorithms , 2004, Parallel Comput..
[57] Geoffrey I. Webb. Efficient search for association rules , 2000, KDD '00.
[58] Zvi M. Kedem,et al. Pincer-Search: A New Algorithm for Discovering the Maximum Frequent Set , 1998, EDBT.
[59] Jiawei Han,et al. BIDE: efficient mining of frequent closed sequences , 2004, Proceedings. 20th International Conference on Data Engineering.
[60] Shi Zhongzhi,et al. Efficiently mining frequent itemsets with compact FP-tree , 2004 .
[61] Balázs Rácz,et al. nonordfp: An FP-growth variation without rebuilding the FP-tree , 2004, FIMI.
[62] Jiawei Han,et al. Frequent pattern mining: current status and future directions , 2007, Data Mining and Knowledge Discovery.
[63] Jean-François Boulicaut,et al. Free-Sets: A Condensed Representation of Boolean Data for the Approximation of Frequency Queries , 2004, Data Mining and Knowledge Discovery.
[64] Ke Wang,et al. Mining frequent item sets by opportunistic projection , 2002, KDD.
[65] Hiroki Arimura,et al. LCM ver. 2: Efficient Mining Algorithms for Frequent/Closed/Maximal Itemsets , 2004, FIMI.
[66] Jian Pei,et al. CLOSET+: searching for the best strategies for mining frequent closed itemsets , 2003, KDD '03.
[67] Roberto J. Bayardo,et al. Efficiently mining long patterns from databases , 1998, SIGMOD '98.
[68] Jaideep Srivastava,et al. Selecting the right interestingness measure for association patterns , 2002, KDD.
[69] Jeffrey F. Naughton,et al. On differentially private frequent itemset mining , 2012, Proc. VLDB Endow..