Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Zero-suppressed BDDs for set manipulation in combinatorial problems
DAC '93 Proceedings of the 30th international Design Automation Conference
Machine Learning
Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Interleaving based variable ordering methods for ordered binary decision diagrams
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
Dynamic variable ordering for ordered binary decision diagrams
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
The multiple variable order problem for binary decision diagrams: theory and practical application
Proceedings of the 2001 Asia and South Pacific Design Automation Conference
Detecting Group Differences: Mining Contrast Sets
Data Mining and Knowledge Discovery
Fast Algorithms for Mining Emerging Patterns
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Mining for empty spaces in large data sets
Theoretical Computer Science - Database theory
Multi-resolution on compressed sets of clauses
ICTAI '00 Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence
Using transposition for pattern discovery from microarray data
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
On detecting differences between groups
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
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 border descriptions of emerging patterns from dataset pairs
Knowledge and Information Systems
Efficient Method of Combinatorial Item Set Analysis Based on Zero-Suppressed BDDs
WIRI '05 Proceedings of the International Workshop on Challenges in Web Information Retrieval and Integration
Top-Down Mining of Interesting Patterns from Very High Dimensional Data
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Discovering interesting holes in data
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Mining statistically important equivalence classes and delta-discriminative emerging patterns
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Mining influential attributes that capture class and group contrast behaviour
Proceedings of the 17th ACM conference on Information and knowledge management
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
Mining Class Contrast Functions by Gene Expression Programming
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Diverging patterns: discovering significant frequency change dissimilarities in large databases
Proceedings of the 18th ACM conference on Information and knowledge management
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Transactions on rough sets XII
On the stimulation of patterns: definitions, calculation method and first usages
ICCS'10 Proceedings of the 18th international conference on Conceptual structures: from information to intelligence
Mining contrast inequalities in numeric dataset
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Using constraints to generate and explore higher order discriminative patterns
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
PRIMA'11 Proceedings of the 14th international conference on Agents in Principle, Agents in Practice
Mining emerging patterns by streaming feature selection
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Sampling minimal frequent boolean (DNF) patterns
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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Patterns of contrast are a very important way of comparing multi-dimensional datasets. Such patterns are able to capture regions of high difference between two classes of data, and are useful for human experts and the construction of classifiers. However, mining such patterns is particularly challenging when the number of dimensions is large. This paper describes a new technique for mining several varieties of contrast pattern, based on the use of Zero-Suppressed Binary Decision Diagrams (ZBDDs), a powerful data structure for manipulating sparse data. We study the mining of both simple contrast patterns, such as emerging patterns, and more novel and complex contrasts, which we call disjunctive emerging patterns. A performance study demonstrates our ZBDD technique is highly scalable, substantially improves on state of the art mining for emerging patterns and can be effective for discovering complex contrasts from datasets with thousands of attributes.