On generating all maximal independent sets
Information Processing Letters
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Bases of Motifs for Generating Repeated Patterns with Wild Cards
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Shuffling biological sequences with motif constraints
Journal of Discrete Algorithms
Sequence Mining Automata: A New Technique for Mining Frequent Sequences under Regular Expressions
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Enumeration aspects of maximal cliques and bicliques
Discrete Applied Mathematics
An efficient polynomial delay algorithm for pseudo frequent itemset mining
DS'07 Proceedings of the 10th international conference on Discovery science
The average complexity of Moore's state minimization algorithm is O(n log log n)
MFCS'10 Proceedings of the 35th international conference on Mathematical foundations of computer science
| Hi-index | 5.23 |
In this paper, we introduce an generic framework for the mining of sequences under various constraints. More precisely, we study the enumeration of all partitions of a word w into multisets of subsequences. We show that using additional predicates, this generator can be used for frequent subsequences and substrings mining. We define the transition graph T"w whose vertices are multisets of words and arcs are transitions between multisets. We show that T"w is a directed acyclic graph and it admits a covering tree. We use T"w to propose a generic algorithm that enumerates all multisets that satisfies a set of predicates, without redundancy.