Association Rules
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[1] Heikki Mannila,et al. A database perspective on knowledge discovery , 1996, CACM.
[2] Daniel Sánchez,et al. A New Framework to Assess Association Rules , 2001, IDA.
[3] Heikki Mannila,et al. Finding interesting rules from large sets of discovered association rules , 1994, CIKM '94.
[4] Wynne Hsu,et al. Pruning and summarizing the discovered associations , 1999, KDD '99.
[5] Sunita Sarawagi,et al. Integrating association rule mining with relational database systems: alternatives and implications , 1998, SIGMOD '98.
[6] Shamkant B. Navathe,et al. Mining for strong negative associations in a large database of customer transactions , 1998, Proceedings 14th International Conference on Data Engineering.
[7] Tomasz Imielinski,et al. Database Mining: A Performance Perspective , 1993, IEEE Trans. Knowl. Data Eng..
[8] Jiawei Han,et al. Mining recurrent items in multimedia with progressive resolution refinement , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).
[9] Shamkant B. Navathe,et al. An Efficient Algorithm for Mining Association Rules in Large Databases , 1995, VLDB.
[10] Wynne Hsu,et al. Discovering the set of fundamental rule changes , 2001, KDD '01.
[11] Rajeev Motwani,et al. Dynamic itemset counting and implication rules for market basket data , 1997, SIGMOD '97.
[12] Jian Pei,et al. Can we push more constraints into frequent pattern mining? , 2000, KDD '00.
[13] Jiawei Han,et al. Discovery of Multiple-Level Association Rules from Large Databases , 1995, VLDB.
[14] Giuseppe Psaila,et al. A New SQL-like Operator for Mining Association Rules , 1996, VLDB.
[15] Tomasz Imielinski,et al. Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.
[16] Peter Clark,et al. Rule Induction with CN2: Some Recent Improvements , 1991, EWSL.
[17] Christos Faloutsos,et al. Ratio Rules: A New Paradigm for Fast, Quantifiable Data Mining , 1998, VLDB.
[18] Padhraic Smyth,et al. An Information Theoretic Approach to Rule Induction from Databases , 1992, IEEE Trans. Knowl. Data Eng..
[19] A. Jaoua,et al. Discovering knowledge from fuzzy concept lattice , 2001 .
[20] Radim Belohlávek,et al. Fuzzy Galois Connections , 1999, Math. Log. Q..
[21] Niall M. Adams,et al. Determining Hit Rate in Pattern Search , 2002, Pattern Detection and Discovery.
[22] Kotagiri Ramamohanarao,et al. Efficient Mining of High Confidience Association Rules without Support Thresholds , 1999, PKDD.
[23] Jiawei Han,et al. Metarule-Guided Mining of Multi-Dimensional Association Rules Using Data Cubes , 1997, KDD.
[24] Dmitry Zelenko. Optimizing Disjunctive Association Rules , 1999, PKDD.
[25] Philip S. Yu,et al. An effective hash-based algorithm for mining association rules , 1995, SIGMOD '95.
[26] Jian Pei,et al. Mining frequent patterns without candidate generation , 2000, SIGMOD 2000.
[27] Laks V. S. Lakshmanan,et al. Exploratory mining and pruning optimizations of constrained associations rules , 1998, SIGMOD '98.
[28] Nicolas Pasquier,et al. Efficient Mining of Association Rules Using Closed Itemset Lattices , 1999, Inf. Syst..
[29] Edith Cohen,et al. Finding interesting associations without support pruning , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).
[30] Hannu T. T. Toivonen,et al. Samplinglarge databases for finding association rules , 1996, VLDB 1996.
[31] Jinyan Li,et al. Efficient mining of emerging patterns: discovering trends and differences , 1999, KDD '99.
[32] Ramakrishnan Srikant,et al. Mining Association Rules with Item Constraints , 1997, KDD.
[33] Dimitrios Gunopulos,et al. Efficient Mining of Spatiotemporal Patterns , 2001, SSTD.
[34] Rajeev Motwani,et al. Beyond market baskets: generalizing association rules to correlations , 1997, SIGMOD '97.
[35] Frank Höppner. Discovery of Core Episodes from Sequences , 2002, Pattern Detection and Discovery.
[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] Bart Goethals,et al. On Supporting Interactive Association Rule Mining , 2000, DaWaK.
[39] Jean-Marc Adamo,et al. Data Mining for Association Rules and Sequential Patterns , 2000, Springer New York.
[40] A. J. Feelders,et al. MAMBO: Discovering Association Rules Based on Conditional Independencies , 2001, IDA.
[41] 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).
[42] Sanjay Ranka,et al. An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases , 1997, KDD.
[43] Rajeev Motwani,et al. Computing Iceberg Queries Efficiently , 1998, VLDB.
[44] Laks V. S. Lakshmanan,et al. Efficient mining of constrained correlated sets , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).
[45] Jiawei Han,et al. A fast distributed algorithm for mining association rules , 1996, Fourth International Conference on Parallel and Distributed Information Systems.
[46] Ramakrishnan Srikant,et al. Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.
[47] Christian Borgelt,et al. Mining molecular fragments: finding relevant substructures of molecules , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..
[48] D. Cheung,et al. Maintenance of Discovered Association Rules: When to update? , 1997, DMKD.
[49] Heikki Mannila,et al. Fast Discovery of Association Rules , 1996, Advances in Knowledge Discovery and Data Mining.
[50] Jiawei Han,et al. Discovery of Spatial Association Rules in Geographic Information Databases , 1995, SSD.
[51] Chris Clifton,et al. Query flocks: a generalization of association-rule mining , 1998, SIGMOD '98.
[52] Jiawei Han,et al. Data Mining: Concepts and Techniques , 2000 .
[53] 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.
[54] Sridhar Ramaswamy,et al. On the Discovery of Interesting Patterns in Association Rules , 1998, VLDB.
[55] Ramakrishnan Srikant,et al. Mining generalized association rules , 1995, Future Gener. Comput. Syst..
[56] Hannu Toivonen,et al. Sampling Large Databases for Association Rules , 1996, VLDB.
[57] Geoffrey I. Webb. Discovering associations with numeric variables , 2001, KDD '01.
[58] Nicolas Pasquier,et al. Discovering Frequent Closed Itemsets for Association Rules , 1999, ICDT.
[59] Roberto J. Bayardo,et al. Efficiently mining long patterns from databases , 1998, SIGMOD '98.
[60] Ramakrishnan Srikant,et al. Mining sequential patterns , 1995, Proceedings of the Eleventh International Conference on Data Engineering.
[61] Jaideep Srivastava,et al. Selecting the right interestingness measure for association patterns , 2002, KDD.
[62] Sridhar Ramaswamy,et al. Cyclic association rules , 1998, Proceedings 14th International Conference on Data Engineering.
[63] Roberto J. Bayardo,et al. Mining the most interesting rules , 1999, KDD '99.
[64] William Frawley,et al. Knowledge Discovery in Databases , 1991 .
[65] Wai-Ho Au,et al. FARM: a data mining system for discovering fuzzy association rules , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).
[66] Balaji Padmanabhan,et al. A Belief-Driven Method for Discovering Unexpected Patterns , 1998, KDD.
[67] Geoffrey I. Webb. Efficient search for association rules , 2000, KDD '00.
[68] Ramakrishnan Srikant,et al. Mining quantitative association rules in large relational tables , 1996, SIGMOD '96.
[69] Srinivasan Parthasarathy,et al. New Algorithms for Fast Discovery of Association Rules , 1997, KDD.
[70] Mohammed J. Zaki. Scalable Algorithms for Association Mining , 2000, IEEE Trans. Knowl. Data Eng..
[71] Yasuhiko Morimoto,et al. Computing Optimized Rectilinear Regions for Association Rules , 1997, KDD.
[72] Marzena Kryszkiewicz. Concise representation of frequent patterns based on disjunction-free generators , 2001, Proceedings 2001 IEEE International Conference on Data Mining.
[73] Hongjun Lu,et al. H-mine: hyper-structure mining of frequent patterns in large databases , 2001, Proceedings 2001 IEEE International Conference on Data Mining.
[74] Mohammed J. Zaki. Generating non-redundant association rules , 2000, KDD '00.
[75] Frank Klawonn,et al. Finding informative rules in interval sequences , 2001, Intell. Data Anal..
[76] Vipin Kumar,et al. Scalable parallel data mining for association rules , 1997, SIGMOD '97.
[77] Nicholas I. Fisher,et al. Bump hunting in high-dimensional data , 1999, Stat. Comput..
[78] Leo Breiman,et al. Classification and Regression Trees , 1984 .
[79] H. Sebastian Seung,et al. Learning the parts of objects by non-negative matrix factorization , 1999, Nature.
[80] M.A.W. Houtsma,et al. Set-Oriented Mining for Association Rules , 1993, ICDE 1993.
[81] Ming-Syan Chen,et al. On mining general temporal association rules in a publication database , 2001, Proceedings 2001 IEEE International Conference on Data Mining.
[82] Geert Wets,et al. Using association rules for product assortment decisions: a case study , 1999, KDD '99.
[83] Gregory Piatetsky-Shapiro,et al. Discovery, Analysis, and Presentation of Strong Rules , 1991, Knowledge Discovery in Databases.
[84] Arun N. Swami,et al. Set-oriented mining for association rules in relational databases , 1995, Proceedings of the Eleventh International Conference on Data Engineering.
[85] Gerd Stumme,et al. Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets , 2000, Computational Logic.
[86] Jiawei Han,et al. Maintenance of discovered association rules in large databases: an incremental updating technique , 1996, Proceedings of the Twelfth International Conference on Data Engineering.
[87] Yehuda Lindell,et al. A Statistical Theory for Quantitative Association Rules , 1999, KDD '99.
[88] Dimitrios Gunopulos,et al. Constraint-Based Rule Mining in Large, Dense Databases , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).
[89] Tomasz Imielinski,et al. An Interval Classifier for Database Mining Applications , 1992, VLDB.
[90] Heikki Mannila,et al. Multiple Uses of Frequent Sets and Condensed Representations (Extended Abstract) , 1996, KDD.
[91] Heikki Mannila,et al. Efficient Algorithms for Discovering Association Rules , 1994, KDD Workshop.
[92] Jinyan Li,et al. Interestingness of Discovered Association Rules in Terms of Neighborhood-Based Unexpectedness , 1998, PAKDD.
[93] Jiawei Han,et al. Meta-Rule-Guided Mining of Association Rules in Relational Databases , 1995, KDOOD/TDOOD.
[94] Daniel Sánchez,et al. Mining Text Data: Special Features and Patterns , 2002, Pattern Detection and Discovery.
[95] Ramakrishnan Srikant,et al. The Quest Data Mining System , 1996, KDD.
[96] Raghu Ramakrishnan,et al. Bottom-up computation of sparse and Iceberg CUBE , 1999, SIGMOD '99.
[97] Viktor Jovanoski,et al. High Confidence Association Rules for Medical Diagnosis , 1999 .
[98] Howard J. Hamilton,et al. Knowledge discovery and measures of interest , 2001 .
[99] Renée J. Miller,et al. Association rules over interval data , 1997, SIGMOD '97.
[100] Yasuhiko Morimoto,et al. Data mining using two-dimensional optimized association rules: scheme, algorithms, and visualization , 1996, SIGMOD '96.
[101] Jian Pei,et al. CMAR: accurate and efficient classification based on multiple class-association rules , 2001, Proceedings 2001 IEEE International Conference on Data Mining.