Incrementally mining high utility patterns based on pre-large concept

References

Page 1

	Year	Citations
Lecture Notes in Computer Science 1205 Industrial Robot the international journal of robotics research and application Lecture RecordingProgramming Language TheoryEngineeringComputer Science 1205Formal Methods	1999	38.7K
Mining association rules between sets of items in large databases Rakesh Agrawal, Tomasz Imieliński, Arun Swami EngineeringBusiness IntelligencePattern DiscoveryLarge DatabasePattern Mining	1993	14.7K
Fast Algorithms for Mining Association Rules in Large Databases Rakesh Agrawal, Ramakrishnan Srikant Very Large Data Bases EngineeringInformation RetrievalData ScienceData MiningFrequent Pattern Mining	1994	9.4K
Data mining: an overview from a database perspective Ming-Syan Chen⋆, Jiawei Han, Philip S. Yu IEEE Transactions on Knowledge and Data Engineering EngineeringMachine LearningBusiness IntelligencePattern MiningBusiness Analytics	1996	2.2K
Dynamic itemset counting and implication rules for market basket data Sergey Brin, Rajeev Motwani, Jeffrey D. Ullman, EngineeringDynamic Itemset CountingBusiness IntelligencePattern DiscoveryPattern Mining	1997	2K
Database mining: a performance perspective R. K. Agrawal, Tomasz Imieliński, A. Swami IEEE Transactions on Knowledge and Data Engineering EngineeringPattern DiscoveryPattern MiningMining MethodsDatabase Mining Problems	1993	1.5K
An effective hash-based algorithm for mining association rules Jong Soo Park, Ming-Syan Chen⋆, Philip S. Yu EngineeringBusiness IntelligencePattern DiscoveryLarge DatabasePattern Mining	1995	1.4K
New algorithms for fast discovery of association rules Mohammed J. Zaki, Srinivasan Parthasarathy, Mitsunori Ogihara,	1997	1.1K
Maintenance of discovered association rules in large databases: an incremental updating technique David W. Cheung, Jiawei Han, Vincent Ng Incremental Updating TechniqueEngineeringPattern DiscoveryPattern MiningInformation Retrieval	2002	804
Dynamic itemset counting and implication rules for market basket data Sergey Brin, Rajeev Motwani, Jeffrey D. Ullman, ACM SIGMOD Record EngineeringDynamic Itemset CountingBusiness IntelligencePattern DiscoveryPattern Mining	1997	605

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