Fast discovery of association rules
Advances in knowledge discovery and data mining
Identification of gene regulatory networks by strategic gene disruptions and gene overexpressions
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Mining generalised disjunctive association rules
Proceedings of the tenth international conference on Information and knowledge management
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Mining for Strong Negative Associations in a Large Database of Customer Transactions
ICDE '98 Proceedings of the Fourteenth 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
Efficient mining of both positive and negative association rules
ACM Transactions on Information Systems (TOIS)
Turning CARTwheels: an alternating algorithm for mining redescriptions
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Algorithms for Mining Closed Itemsets and Their Lattice Structure
IEEE Transactions on Knowledge and Data Engineering
Mining positive and negative association rules: an approach for confined rules
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Reasoning about sets using redescription mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Compositional mining of multirelational biological datasets
ACM Transactions on Knowledge Discovery from Data (TKDD)
Data & Knowledge Engineering
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
Alattin: mining alternative patterns for defect detection
Automated Software Engineering
Mining disjunctive minimal generators with TitanicOR
Expert Systems with Applications: An International Journal
Sampling minimal frequent boolean (DNF) patterns
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
A Framework for Synthesizing Arbitrary Boolean Queries Induced by Frequent Itemsets
International Journal of Knowledge-Based Organizations
POSTER: A semantic-aware approach to reasoning about network traffic relations
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Key roles of closed sets and minimal generators in concise representations of frequent patterns
Intelligent Data Analysis
| Hi-index | 0.00 |
We introduce a novel framework, called BLOSOM, for mining (frequent) boolean expressions over binary-valued datasets. We organize the space of boolean expressions into four categories: pure conjunctions, pure disjunctions, conjunction of disjunctions, and disjunction of conjunctions. We focus on mining the simplest expressions the minimal generators for each class. We also propose a closure operator for each class that yields closed boolean expressions. BLOSOM efficiently mines frequent boolean expressions by utilizing a number of methodical pruning techniques. Experiments showcase the behavior of BLOSOM, and an application study on a real dataset is also given.