Mining frequent patterns without candidate generation
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VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
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ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
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ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Efficient Data Mining for Maximal Frequent Subtrees
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
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IEEE Transactions on Knowledge and Data Engineering
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ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
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Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
4th International Workshop on Mining Software Repositories (MSR 2007)
ICSE COMPANION '07 Companion to the proceedings of the 29th International Conference on Software Engineering
Hierarchical program representation for program element matching
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Frequent Itemset Mining in Multirelational Databases
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Mining Musical Patterns: Identification of Transposed Motives
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Mining Tree-Based Frequent Patterns from XML
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Reverse engineering user interfaces for interactive database conceptual analysis
CAiSE'10 Proceedings of the 22nd international conference on Advanced information systems engineering
Frequent tree pattern mining: A survey
Intelligent Data Analysis
Mining transposed motifs in music
Journal of Intelligent Information Systems
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Many data mining problems can be represented with non-linear data structures like trees. In this paper, we introduce a scalable algorithm to mine partially-ordered trees. Our algorithm, POTMiner, is able to identify both induced and embedded subtrees and, as special cases, it can handle both completely ordered and completely unordered trees (i.e. the particular situations existing algorithms address).