A quickstart in frequent structure mining can make a difference
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Closed and Maximal Frequent Subtrees from Databases of Labeled Rooted Trees
IEEE Transactions on Knowledge and Data Engineering
Efficiently Mining Frequent Trees in a Forest: Algorithms and Applications
IEEE Transactions on Knowledge and Data Engineering
AMIOT: Induced Ordered Tree Mining in Tree-Structured Databases
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Extending taxonomic visualisation to incorporate synonymy and structural markers
Information Visualization - Special issue: Bioinformatics visualization
Efficiently Mining Frequent Embedded Unordered Trees
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Frequent Subtree Mining - An Overview
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Tree model guided candidate generation for mining frequent subtrees from XML documents
ACM Transactions on Knowledge Discovery from Data (TKDD)
PCITMiner: prefix-based closed induced tree miner for finding closed induced frequent subtrees
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Mining Frequent Closed Unordered Trees Through Natural Representations
ICCS '07 Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications
An integrated, generic approach to pattern mining: data mining template library
Data Mining and Knowledge Discovery
A novel Boolean algebraic framework for association and pattern mining
WSEAS Transactions on Computers
Bottom-up discovery of frequent rooted unordered subtrees
Information Sciences: an International Journal
Mining Unordered Distance-Constrained Embedded Subtrees
DS '08 Proceedings of the 11th International Conference on Discovery Science
Finding Frequent Patterns from Compressed Tree-Structured Data
DS '08 Proceedings of the 11th International Conference on Discovery Science
U3 - Mning Unordered Embedded Subtrees Using TMG Candidate Generation
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
A Boolean algebraic framework for association and pattern mining
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
Efficient rule based structural algorithms for classification of tree structured data
Intelligent Data Analysis
The Gaston Tool for Frequent Subgraph Mining
Electronic Notes in Theoretical Computer Science (ENTCS)
Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams
Proceedings of the 2010 conference on Adaptive Stream Mining: Pattern Learning and Mining from Evolving Data Streams
BUXMiner: an efficient bottom-up approach to mining XML query patterns
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
Mining induced and embedded subtrees in ordered, unordered, and partially-ordered trees
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
MARGIN: Maximal frequent subgraph mining
ACM Transactions on Knowledge Discovery from Data (TKDD)
POTMiner: mining ordered, unordered, and partially-ordered trees
Knowledge and Information Systems
Frequent tree pattern mining: A survey
Intelligent Data Analysis
Model guided algorithm for mining unordered embedded subtrees
Web Intelligence and Agent Systems
Mining frequent patterns from XML data: Efficient algorithms and design trade-offs
Expert Systems with Applications: An International Journal
Finding trees from unordered 0–1 data
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Extraction of interesting financial information from heterogeneous XML-Based data
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
To see the wood for the trees: mining frequent tree patterns
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
WISE'06 Proceedings of the 7th international conference on Web Information Systems
Mining patterns from longitudinal studies
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II
Efficiently Mining Frequent Embedded Unordered Trees
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Frequent Subtree Mining - An Overview
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Mining Induced/Embedded Subtrees using the Level of Embedding Constraint
Fundamenta Informaticae
Error mining on dependency trees
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
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Tree structures are used extensively in domains suchas computational biology, pattern recognition, XMLdatabases, computer networks, and so on. In this paper,we present HybridTreeMiner, a computationally efficientalgorithm that discovers all frequently occurringsubtrees in a database of rooted unordered trees. The algorithmmines frequent subtrees by traversing an enumerationtree that systematically enumerates all subtrees. The enumerationtree is defined based on a novel canonicalform for rooted unordered trees-the breadth-first canonicalform (BFCF). By extending the definitions of our canonicalform and enumeration tree to free trees, our algorithmcan efficiently handle databases of free trees as well.We study the performance of our algorithms through extensiveexperiments based on both synthetic data and datasetsfrom real applications. The experiments show that our algorithmis competitive in comparison to known rooted treemining algorithms and is faster by one to two orders ofmagnitudes compared to a known algorithm for mining frequentfree trees.