Efficient mining of association rules using closed itemset lattices
Information Systems
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Algorithms for association rule mining — a general survey and comparison
ACM SIGKDD Explorations Newsletter
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Real world performance of association rule algorithms
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Towards long pattern generation in dense databases
ACM SIGKDD Explorations Newsletter
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Free-Sets: A Condensed Representation of Boolean Data for the Approximation of Frequency Queries
Data Mining and Knowledge Discovery
Parallel and Distributed Association Mining: A Survey
IEEE Concurrency
Concise Representation of Frequent Patterns Based on Disjunction-Free Generators
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Mining All Non-derivable Frequent Itemsets
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Fast algorithms for mining association rules and sequential patterns
Fast algorithms for mining association rules and sequential patterns
Partitioning Large Data to Scale up Lattice-Based Algorithm
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
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
Carpenter: finding closed patterns in long biological datasets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
FARMER: finding interesting rule groups in microarray datasets
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Efficiently mining frequent itemsets from very large databases
Efficiently mining frequent itemsets from very large databases
Fast and Memory Efficient Mining of Frequent Closed Itemsets
IEEE Transactions on Knowledge and Data Engineering
A Thorough Experimental Study of Datasets for Frequent Itemsets
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Essential patterns: a perfect cover of frequent patterns
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Finding all frequent patterns starting from the closure
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
A divide and conquer approach for deriving partially ordered sub-structures
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
A survey on condensed representations for frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
Efficient mining of understandable patterns from multivariate interval time series
Data Mining and Knowledge Discovery
An efficient algorithm for mining closed inter-transaction itemsets
Data & Knowledge Engineering
Finding Frequent Closed Itemsets in Sliding Window in Linear Time
IEICE - Transactions on Information and Systems
Data & Knowledge Engineering
A new generic basis of "factual" and "implicative" association rules
Intelligent Data Analysis
A novel approach for privacy mining of generic basic association rules
Proceedings of the ACM first international workshop on Privacy and anonymity for very large databases
ACM SIGKDD Explorations Newsletter
An efficient algorithm for mining frequent maximal and closed itemsets
International Journal of Hybrid Intelligent Systems
Using a reinforced concept lattice to incrementally mine association rules from closed itemsets
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
GC-tree: a fast online algorithm for mining frequent closed itemsets
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
TGC-tree: an online algorithm tracing closed itemset and transaction set simultaneously
LKR'08 Proceedings of the 3rd international conference on Large-scale knowledge resources: construction and application
Succinct system of minimal generators: a thorough study, limitations and new definitions
CLA'06 Proceedings of the 4th international conference on Concept lattices and their applications
Frequent regular itemset mining
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining closed itemsets in data stream using formal concept analysis
DaWaK'10 Proceedings of the 12th international conference on Data warehousing and knowledge discovery
DS'10 Proceedings of the 13th international conference on Discovery science
Mining minimal non-redundant association rules using frequent itemsets lattice
International Journal of Intelligent Systems Technologies and Applications
Mining frequent itemsets from multidimensional databases
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Formal context coverage based on isolated labels: An efficient solution for text feature extraction
Information Sciences: an International Journal
DBV-Miner: A Dynamic Bit-Vector approach for fast mining frequent closed itemsets
Expert Systems with Applications: An International Journal
A new approach for association rule mining and bi-clustering using formal concept analysis
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
Information Sciences: an International Journal
A lattice-based approach for mining most generalization association rules
Knowledge-Based Systems
Speeding up correlation search for binary data
Pattern Recognition Letters
Interesting pattern mining in multi-relational data
Data Mining and Knowledge Discovery
Key roles of closed sets and minimal generators in concise representations of frequent patterns
Intelligent Data Analysis
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As a side effect of the digitalization of unprecedented amount of data, traditional retrieval tools proved to be unable to extract hidden and valuable knowledge. Data Mining, with a clear promise to provide adequate tools and/or techniques to do so, is the discovery of hidden information that can be retrieved from datasets. In this paper, we present a structural and analytical survey of frequent closed itemset (FCI) based algorithms for mining association rules. Indeed, we provide a structural classification, in four categories, and a comparison of these algorithms based on criteria that we introduce. We also present an analytical comparison of FCI-based algorithms using benchmark dense and sparse datasets as well as "worst case" datasets. Aiming to stand beyond classical performance analysis, we intend to provide a focal point on performance analysis based on memory consumption and advantages and/or limitations of optimization strategies, used in the FCI-based algorithms.