Fast discovery of association rules
Advances in knowledge discovery and data mining
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Scalable Algorithms for Association Mining
IEEE Transactions on Knowledge and Data Engineering
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
Proceedings of the 17th International Conference on Data Engineering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Efficiently mining frequent trees in a forest
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
CLOSET+: searching for the best strategies for mining frequent closed itemsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
CloseGraph: mining closed frequent graph patterns
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
BIDE: Efficient Mining of Frequent Closed Sequences
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Advances in frequent itemset mining implementations: report on FIMI'03
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
DRYADE: A New Approach for Discovering Closed Frequent Trees in Heterogeneous Tree Databases
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
On horn axiomatizations for sequential data
ICDT'05 Proceedings of the 10th international conference on Database Theory
A model for managing collections of patterns
Proceedings of the 2007 ACM symposium on Applied computing
Extracting spatiotemporal human activity patterns in assisted living using a home sensor network
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Mining adaptively frequent closed unlabeled rooted trees in data streams
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
An integrated, generic approach to pattern mining: data mining template library
Data Mining and Knowledge Discovery
A novel Boolean algebraic framework for association and pattern mining
WSEAS Transactions on Computers
A Boolean algebraic framework for association and pattern mining
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
Mining constraint-based patterns using automatic relaxation
Intelligent Data Analysis
Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams
Proceedings of the 2010 conference on Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams
Mining frequent closed trees in evolving data streams
Intelligent Data Analysis - Ubiquitous Knowledge Discovery
Data Mining and Knowledge Discovery
Towards bounding sequential patterns
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Towards generic pattern mining
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Spatial indexing for scalability in FCA
ICFCA'06 Proceedings of the 4th international conference on Formal Concept Analysis
On nested palindromes in clickstream data
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Graph-Based Modelling of Concurrent Sequential Patterns
International Journal of Data Warehousing and Mining
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Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and useful patterns in massive, complex datasets. In this paper we propose the Data Mining Template Library, a collection of generic containers and algorithms for FPM, as well as persistency and database management classes. DMTL provides a systematic solution to a whole class of common FPM tasks like itemset, sequence, tree and graph mining. DMTL is extensible, scalable, and high-performance for rapid response on massive datasets. Our experiments show that DMTL is competitive with special purpose algorithms designed for a particular pattern type, especially as database sizes increase.