Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 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
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Using a Hash-Based Method with Transaction Trimming for Mining Association Rules
IEEE Transactions on Knowledge and Data Engineering
Scalable Algorithms for Association Mining
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
Proceedings of the 17th International Conference on Data Engineering
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Mining Top.K Frequent Closed Patterns without Minimum Support
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
SmartMiner: A Depth First Algorithm Guided by Tail Information for Mining Maximal Frequent Itemsets
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
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
Fast vertical mining using diffsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Frequent Itemsets from Secondary Memory
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Star-cubing: computing iceberg cubes by top-down and bottom-up integration
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Mining lossless closed frequent patterns with weight constraints
Knowledge-Based Systems
BitTableFI: An efficient mining frequent itemsets algorithm
Knowledge-Based Systems
Mining statistically important equivalence classes and delta-discriminative emerging patterns
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
From frequent itemsets to semantically meaningful visual patterns
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Transactions on Knowledge and Data Engineering
Isolated items discarding strategy for discovering high utility itemsets
Data & Knowledge Engineering
An approach to mining bundled commodities
Knowledge-Based Systems
An efficient technique for incremental updating of association rules
International Journal of Hybrid Intelligent Systems
Index-BitTableFI: An improved algorithm for mining frequent itemsets
Knowledge-Based Systems
Mining GPS traces and visual words for event classification
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Efficient single-pass frequent pattern mining using a prefix-tree
Information Sciences: an International Journal
Efficient Single-Pass Mining of Weighted Interesting Patterns
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Efficient mining of interesting weighted patterns from directed graph traversals
Integrated Computer-Aided Engineering
Closed patterns meet n-ary relations
ACM Transactions on Knowledge Discovery from Data (TKDD)
Post-processing of associative classification rules using closed sets
Expert Systems with Applications: An International Journal
Mining high utility patterns in incremental databases
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
A framework for mining top-k frequent closed itemsets using order preserving generators
Proceedings of the 2nd Bangalore Annual Compute Conference
Deriving strong association mining rules using a dependency criterion, the lift measure
International Journal of Data Analysis Techniques and Strategies
Handling Dynamic Weights in Weighted Frequent Pattern Mining
IEICE - Transactions on Information and Systems
Multi-level Frequent Pattern Mining
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
Minimum description length principle: generators are preferable to closed patterns
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Two-phase algorithms for a novel utility-frequent mining model
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Using a cosine-type measure to derive strong association mining rules
International Journal of Knowledge Engineering and Data Mining
Information Sciences: an International Journal
An efficient algorithm for incremental mining of temporal association rules
Data & Knowledge Engineering
Negative correlations in collaboration: concepts and algorithms
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
BISC: A bitmap itemset support counting approach for efficient frequent itemset mining
ACM Transactions on Knowledge Discovery from Data (TKDD)
Algorithms for mining frequent itemsets in static and dynamic datasets
Intelligent Data Analysis
Approximate weighted frequent pattern mining with/without noisy environments
Knowledge-Based Systems
An improved frequent pattern growth method for mining association rules
Expert Systems with Applications: An International Journal
Experimental study on fighters behaviors mining
Expert Systems with Applications: An International Journal
Mining minimal non-redundant association rules using frequent itemsets lattice
International Journal of Intelligent Systems Technologies and Applications
Boosting part-sense multi-feature learners toward effective object detection
Computer Vision and Image Understanding
Effective utility mining with the measure of average utility
Expert Systems with Applications: An International Journal
HUC-Prune: an efficient candidate pruning technique to mine high utility patterns
Applied Intelligence
Interestingness measures for association rules: Combination between lattice and hash tables
Expert Systems with Applications: An International Journal
An improved association rules mining method
Expert Systems with Applications: An International Journal
A parallel algorithm for computing borders
Proceedings of the 20th ACM international conference on Information and knowledge management
A new mining approach for uncertain databases using CUFP trees
Expert Systems with Applications: An International Journal
Efficient aggregate licenses validation in DRM
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
DBV-Miner: A Dynamic Bit-Vector approach for fast mining frequent closed itemsets
Expert Systems with Applications: An International Journal
Single-pass incremental and interactive mining for weighted frequent patterns
Expert Systems with Applications: An International Journal
A practical approximation algorithm for optimal k-anonymity
Data Mining and Knowledge Discovery
An efficient mining algorithm for maximal weighted frequent patterns in transactional databases
Knowledge-Based Systems
Interactive mining of high utility patterns over data streams
Expert Systems with Applications: An International Journal
The retrieval of motion event by associations of temporal frequent pattern growth
Future Generation Computer Systems
Recent frequent itemsets mining over data streams
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
A fast algorithm for frequent itemset mining using Patricia* structures
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
ShrFP-tree: an efficient tree structure for mining share-frequent patterns
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
A lattice-based approach for mining most generalization association rules
Knowledge-Based Systems
MFIBlocks: An effective blocking algorithm for entity resolution
Information Systems
Sliding window based weighted maximal frequent pattern mining over data streams
Expert Systems with Applications: An International Journal
Fast mining Top-Rank-k frequent patterns by using Node-lists
Expert Systems with Applications: An International Journal
Mining maximal frequent patterns by considering weight conditions over data streams
Knowledge-Based Systems
Efficient frequent pattern mining based on Linear Prefix tree
Knowledge-Based Systems
An efficient method for mining frequent itemsets with double constraints
Engineering Applications of Artificial Intelligence
MEI: An efficient algorithm for mining erasable itemsets
Engineering Applications of Artificial Intelligence
Mining high utility itemsets by dynamically pruning the tree structure
Applied Intelligence
Minimally infrequent itemset mining using pattern-growth paradigm and residual trees
Proceedings of the 17th International Conference on Management of Data
Efficient mining of maximal correlated weight frequent patterns
Intelligent Data Analysis
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Efficient algorithms for mining frequent itemsets are crucial for mining association rules as well as for many other data mining tasks. Methods for mining frequent itemsets have been implemented using a prefix-tree structure, known as an FP-tree, for storing compressed information about frequent itemsets. Numerous experimental results have demonstrated that these algorithms perform extremely well. In this paper, we present a novel FP-array technique that greatly reduces the need to traverse FP-trees, thus obtaining significantly improved performance for FP-tree-based algorithms. Our technique works especially well for sparse data sets. Furthermore, we present new algorithms for mining all, maximal, and closed frequent itemsets. Our algorithms use the FP-tree data structure in combination with the FP-array technique efficiently and incorporate various optimization techniques. We also present experimental results comparing our methods with existing algorithms. The results show that our methods are the fastest for many cases. Even though the algorithms consume much memory when the data sets are sparse, they are still the fastest ones when the minimum support is low. Moreover, they are always among the fastest algorithms and consume less memory than other methods when the data sets are dense.