Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Efficient parallel data mining for association rules
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Extracting optimal association rules over numeric attributes
ACM-SE 36 Proceedings of the 36th annual Southeast regional conference
Online algorithms for finding profile association rules
Proceedings of the seventh international conference on Information and knowledge management
Discovering All Most Specific Sentences by Randomized Algorithms
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Using machine learning to improve information access
Using machine learning to improve information access
Genetic programming for association rules on card sorting data
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
BLOSOM: a framework for mining arbitrary boolean expressions
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Search result summarization and disambiguation via contextual dimensions
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Generalizing the notion of confidence
Knowledge and Information Systems
SemGrAM: integrating semantic graphs into association rule mining
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Using Highly Expressive Contrast Patterns for Classification - Is It Worthwhile?
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Data & Knowledge Engineering
A relational approach for discovering frequent patterns with disjunctions
DaWaK'10 Proceedings of the 12th international conference on Data warehousing and knowledge discovery
An XML format for association rule models based on the GUHA method
RuleML'10 Proceedings of the 2010 international conference on Semantic web rules
Generalization of association rules through disjunction
Annals of Mathematics and Artificial Intelligence
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
Key roles of closed sets and minimal generators in concise representations of frequent patterns
Intelligent Data Analysis
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This paper introduces generalised disjunctive association rules such as "People who buy bread also buy butter jam", and "People who buy either raincoats or umbrellas also buy flashlights". A generalised disjunctive association rule allows the disjunction of conjuncts, "People who buy jackets also buy bow ties or neckties and tiepins". Such rules capture contextual inter-relationships among items.Given a context (antecedent), there may be a large number of generalised disjunctive association rules that satisfy the minsupp and minconf constraints. It is computationally expensive to find all such rules. We present algorithm thrifty traverse which borrows concepts such as subsumption from propositional logic to mine a subset of such rules in a computationally feasible way. We experimented with our algorithm on US census data as well as transaction data from a grocery superstore to demonstrate its computational feasibility, utility and scalability.