Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A fast distributed algorithm for mining association rules
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Parallel and Distributed Association Mining: A Survey
IEEE Concurrency
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Using a Hash-Based Method with Transaction Trimming for Mining Association Rules
IEEE Transactions on Knowledge and Data Engineering
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
DualMiner: a dual-pruning algorithm for itemsets with constraints
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
OSSM: A Segmentation Approach to Optimize Frequency Counting
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
T-Trees, Vertical Partitioning and Distributed Association Rule Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Efficient dynamic mining of constrained frequent sets
ACM Transactions on Database Systems (TODS)
Efficient closed pattern mining in the presence of tough block constraints
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
On Closed Constrained Frequent Pattern Mining
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
A high-performance distributed algorithm for mining association rules
Knowledge and Information Systems
CanTree: A Tree Structure for Efficient Incremental Mining of Frequent Patterns
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Parallel Leap: Large-Scale Maximal Pattern Mining in a Distributed Environment
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
Online analytical mining association rules using Chi-square test
International Journal of Business Intelligence and Data Mining
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With the advance in technology, wireless sensor networks have been widely used in many application areas such as agricultural and environmental monitoring. Sensors distributed in these networks serve as good sources for data. This calls for distributed data mining, which searches for implicit, previously unknown, and potentially useful patterns that might be embedded in the distributed data. Many existing distributed data mining algorithms do not allow users to express the patterns to be mined according to their intension via the use of constraints. Consequently, these unconstrained mining algorithms can yield numerous patterns that are not interesting to users. In this paper, we propose an efficient tree-based system for mining patterns that satisfy user-defined constraints from a distributed environment such as a wireless sensor network. Experimental results show effectiveness of our proposed system.