ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
Discovery of Temporal Patterns. Learning Rules about the Qualitative Behaviour of Time Series
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Frequent Closures as a Concise Representation for Binary Data Mining
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
BIDE: Efficient Mining of Frequent Closed Sequences
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Approximating a collection of frequent sets
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Non-Redundant Association Rules
Data Mining and Knowledge Discovery
Temporal classification: extending the classification paradigm to multivariate time series
Temporal classification: extending the classification paradigm to multivariate time series
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Mining condensed frequent-pattern bases
Knowledge and Information Systems
Learning models and formulas of a temporal event logic
Learning models and formulas of a temporal event logic
Fast and Memory Efficient Mining of Frequent Closed Itemsets
IEEE Transactions on Knowledge and Data Engineering
Discovering Frequent Arrangements of Temporal Intervals
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
On condensed representations of constrained frequent patterns
Knowledge and Information Systems
Algorithms for time series knowledge mining
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering Frequent Closed Partial Orders from Strings
IEEE Transactions on Knowledge and Data Engineering
\delta-Tolerance Closed Frequent Itemsets
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Data Mining and Knowledge Discovery
Mining Nonambiguous Temporal Patterns for Interval-Based Events
IEEE Transactions on Knowledge and Data Engineering
Frequent Closed Sequence Mining without Candidate Maintenance
IEEE Transactions on Knowledge and Data Engineering
Efficient mining of understandable patterns from multivariate interval time series
Data Mining and Knowledge Discovery
Unsupervised pattern mining from symbolic temporal data
ACM SIGKDD Explorations Newsletter - Special issue on data mining for health informatics
Mining conjunctive sequential patterns
Data Mining and Knowledge Discovery
Constraint programming for itemset mining
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Quantitative evaluation of approximate frequent pattern mining algorithms
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Discovery of Frequent Approximate Sequential Patterns
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Efficient algorithms for incremental maintenance of closed sequential patterns in large databases
Data & Knowledge Engineering
Compressing the Set of Frequent Sequential Patterns
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 05
One in a million: picking the right patterns
Knowledge and Information Systems
Finding Good Itemsets by Packing Data
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Sequence Data Mining
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Compression picks item sets that matter
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Knowledge and Information Systems
A survey on condensed representations for frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
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We present a new approach to mining sequential patterns that significantly reduces the number of patterns reported, favoring longer patterns and suppressing shorter patterns with similar frequencies. This is achieved by mining only margin-closed patterns whose support differs by more than some margin from any extension. Our approach extends the efficient BIDE algorithm to enforce the margin constraint. The set of margin-closed patterns can be significantly smaller than a set of just closed patterns while retaining the most important information about the dataset. This is shown by an extensive empirical evaluation on six real life databases.