Molecular feature mining in HIV data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data
Machine Learning
Feature Construction with Version Spaces for Biochemical Applications
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Optimized Substructure Discovery for Semi-structured Data
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Efficiently mining frequent trees in a forest
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Molecular Fragments: Finding Relevant Substructures of Molecules
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Computing Frequent Graph Patterns from Semistructured Data
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
TreeFinder: a First Step towards XML Data Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
ISTCS '97 Proceedings of the Fifth Israel Symposium on the Theory of Computing Systems (ISTCS '97)
Indexing and Mining Free Trees
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
The levelwise version space algorithm and its application to molecular fragment finding
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
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
TRIPS and TIDES: new algorithms for tree mining
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Frequent Subtree Mining - An Overview
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Mining frequent tree-like patterns in large datasets
Data & Knowledge Engineering
Margin-based first-order rule learning
Machine Learning
Tree model guided candidate generation for mining frequent subtrees from XML documents
ACM Transactions on Knowledge Discovery from Data (TKDD)
Mining tree-structured data on multicore systems
Proceedings of the VLDB Endowment
The Gaston Tool for Frequent Subgraph Mining
Electronic Notes in Theoretical Computer Science (ENTCS)
Mining closed frequent free trees in graph databases
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
POTMiner: mining ordered, unordered, and partially-ordered trees
Knowledge and Information Systems
Frequent tree pattern mining: A survey
Intelligent Data Analysis
Adapted transfer of distance measures for quantitative structure-activity relationships
DS'10 Proceedings of the 13th international conference on Discovery science
Mining graphs with constraints on symmetry and diameter
WAIM'10 Proceedings of the 2010 international conference on Web-age information management
Efficient subtree inclusion testing in subtree discovering applications
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
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
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
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In recent years, researchers in graph mining have been exploring linear paths as well as subgraphs as pattern languages. In this paper, we are investigating the middle ground between these two extremes: mining free (that is, unrooted) trees in graph data. The motivation for this is the need to upgrade linear path patterns, while avoiding complexity issues with subgraph patterns. Starting from such complexity considerations, we are defining free trees and their canonical form, before we present FreeTreeMiner, an algorithm making efficient use of this canonical form during search. Experiments with two datasets from the National Cancer Institute's Developmental Therapeutics Program (DTP), anti-HIV and anti-cancer screening data, are reported.