Bottom-up computation of sparse and Iceberg CUBE
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Turbo-charging vertical mining of large databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
New Algorithms for Fast Discovery of Association Rules
New Algorithms for Fast Discovery of Association Rules
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
FARMER: finding interesting rule groups in microarray datasets
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Advances in frequent itemset mining implementations: report on FIMI'03
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
TFP: An Efficient Algorithm for Mining Top-K Frequent Closed Itemsets
IEEE Transactions on Knowledge and Data Engineering
Relative risk and odds ratio: a data mining perspective
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Mining top-K covering rule groups for gene expression data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Mining closed relational graphs with connectivity constraints
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
On discovery of maximal confident rules without support pruning in microarray data
Proceedings of the 5th international workshop on Bioinformatics
Frequent closed itemset based algorithms: a thorough structural and analytical survey
ACM SIGKDD Explorations Newsletter
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent closed cubes in 3D datasets
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Mining association rules in very large clustered domains
Information Systems
The role mining problem: finding a minimal descriptive set of roles
Proceedings of the 12th ACM symposium on Access control models and technologies
High Confidence Rule Mining for Microarray Analysis
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
CSV: visualizing and mining cohesive subgraphs
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Artificial Intelligence in Medicine
A new concise representation of frequent itemsets using generators and a positive border
Knowledge and Information Systems
Closed patterns meet n-ary relations
ACM Transactions on Knowledge Discovery from Data (TKDD)
Top-down mining of frequent closed patterns from very high dimensional data
Information Sciences: an International Journal
A framework for mining top-k frequent closed itemsets using order preserving generators
Proceedings of the 2nd Bangalore Annual Compute Conference
Multi-level Frequent Pattern Mining
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
Edge-RMP: Minimizing administrative assignments for role-based access control
Journal of Computer Security
Minimum description length principle: generators are preferable to closed patterns
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Mining Discriminant Sequential Patterns for Aging Brain
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
Mining High-Correlation Association Rules for Inferring Gene Regulation Networks
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Predicting protein-protein interactions using numerical associational features
CIBCB'09 Proceedings of the 6th Annual IEEE conference on Computational Intelligence in Bioinformatics and Computational Biology
Efficient mining under rich constraints derived from various datasets
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
On approximating minimum infrequent and maximum frequent sets
DS'07 Proceedings of the 10th international conference on Discovery science
The role mining problem: A formal perspective
ACM Transactions on Information and System Security (TISSEC)
New approach for the sequential pattern mining of high-dimensional sequence databases
Decision Support Systems
Finding closed frequent item sets by intersecting transactions
Proceedings of the 14th International Conference on Extending Database Technology
Classifying microarray data with association rules
Proceedings of the 2011 ACM Symposium on Applied Computing
Database transposition for constrained (closed) pattern mining
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
TP+close: mining frequent closed patterns in gene expression datasets
VDMB'06 Proceedings of the First international conference on Data Mining and Bioinformatics
Local pattern discovery in Array-CGH data
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Biologically relevant association rules for classification of microarray data
ACM SIGAPP Applied Computing Review
Efficient colossal pattern mining in high dimensional datasets
Knowledge-Based Systems
Contrast mining from interesting subgroups
Bisociative Knowledge Discovery
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Sequential pattern mining -- approaches and algorithms
ACM Computing Surveys (CSUR)
Closed and noise-tolerant patterns in n-ary relations
Data Mining and Knowledge Discovery
DisClose: discovering colossal closed itemsets via a memory efficient compact row-tree
PAKDD'12 Proceedings of the 2012 Pacific-Asia conference on Emerging Trends in Knowledge Discovery and Data Mining
An efficient and scalable algorithm for mining maximal
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
Key roles of closed sets and minimal generators in concise representations of frequent patterns
Intelligent Data Analysis
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The growth of bioinformatics has resulted in datasets with new characteristics. These datasets typically contain a large number of columns and a small number of rows. For example, many gene expression datasets may contain 10,000-100,000 columns but only 100-1000 rows.Such datasets pose a great challenge for existing (closed) frequent pattern discovery algorithms, since they have an exponential dependence on the average row length. In this paper, we describe a new algorithm called CARPENTER that is specially designed to handle datasets having a large number of attributes and relatively small number of rows. Several experiments on real bioinformatics datasets show that CARPENTER is orders of magnitude better than previous closed pattern mining algorithms like CLOSET and CHARM.