Global partial orders from sequential data
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering local structure in gene expression data: the order-preserving submatrix problem
Proceedings of the sixth annual international conference on Computational biology
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering Frequent Closed Partial Orders from Strings
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
Permu-pattern: discovery of mutable permutation patterns with proximity constraint
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
A novel Boolean algebraic framework for association and pattern mining
WSEAS Transactions on Computers
CONTOUR: an efficient algorithm for discovering discriminating subsequences
Data Mining and Knowledge Discovery
A Boolean algebraic framework for association and pattern mining
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
Fast mining of non-derivable episode rules in complex sequences
MDAI'11 Proceedings of the 8th international conference on Modeling decisions for artificial intelligence
Efficient Mining of Gap-Constrained Subsequences and Its Various Applications
ACM Transactions on Knowledge Discovery from Data (TKDD)
Sequential pattern mining -- approaches and algorithms
ACM Computing Surveys (CSUR)
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Mining ordering information from sequence data is an important data mining task. Sequential pattern mining [1] can be regarded as mining frequent segments of total orders from sequence data. However, sequential patterns are often insufficient to concisely capture the general ordering information.