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Artificial Intelligence - Special issue: AI research in Japan
An Algorithm for Subgraph Isomorphism
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Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Discovery of Frequent Episodes in Event Sequences
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Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Structural Machine Learning with Galois Lattice and Graphs
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Strong Lower Bounds on the Approximability of some NPO PB-Complete Maximization Problems
MFCS '95 Proceedings of the 20th International Symposium on Mathematical Foundations of Computer Science
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
The predictive toxicology evaluation challenge
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
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
Faster association rules for multiple relations
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Mining Significant Pairs of Patterns from Graph Structures with Class Labels
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
State of the art of graph-based data mining
ACM SIGKDD Explorations Newsletter
Frequent free tree discovery in graph data
Proceedings of the 2004 ACM symposium on Applied computing
Eigenspace-based anomaly detection in computer systems
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
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Efficiently Mining Frequent Trees in a Forest: Algorithms and Applications
IEEE Transactions on Knowledge and Data Engineering
Discovering frequent topological structures from graph datasets
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Finding Frequent Patterns in a Large Sparse Graph*
Data Mining and Knowledge Discovery
Frequency-based views to pattern collections
Discrete Applied Mathematics - Special issue: Discrete mathematics & data mining II (DM & DM II)
Frequent subgraph mining in outerplanar graphs
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering Frequent Graph Patterns Using Disjoint Paths
IEEE Transactions on Knowledge and Data Engineering
A Dichotomic Search Algorithm for Mining and Learning in Domain-Specific Logics
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
A General Framework for Mining Frequent Subgraphs from Labeled Graphs
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Graph-based Relational Learning with Application to Security
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Constructing a Decision Tree for Graph-Structured Data and its Applications
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Mining unconnected patterns in workflows
Information Systems
IEEE Transactions on Knowledge and Data Engineering
Graph-Based Analysis of Human Transfer Learning Using a Game Testbed
IEEE Transactions on Knowledge and Data Engineering
Tracing and cataloguing knowledge in an e-health cardiology environment
Journal of Biomedical Informatics
CSV: visualizing and mining cohesive subgraphs
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Index-BitTableFI: An improved algorithm for mining frequent itemsets
Knowledge-Based Systems
User Assisted Substructure Extraction in Molecular Data Mining
MDA '08 Proceedings of the 3rd international conference on Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry
DB-FSG: An SQL-Based Approach for Frequent Subgraph Mining
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
An integrated, generic approach to pattern mining: data mining template library
Data Mining and Knowledge Discovery
Graph kernels based on tree patterns for molecules
Machine Learning
Pruning Strategies Based on the Upper Bound of Information Gain for Discriminative Subgraph Mining
Knowledge Acquisition: Approaches, Algorithms and Applications
APPT '09 Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies
HDB-Subdue: A Scalable Approach to Graph Mining
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
A query language for analyzing networks
Proceedings of the 18th ACM conference on Information and knowledge management
Extracting common design patterns from a set of solid models
Computer-Aided Design
Mining graph patterns efficiently via randomized summaries
Proceedings of the VLDB Endowment
Mining Tree-Based Frequent Patterns from XML
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Frequency-based views to pattern collections
Discrete Applied Mathematics - Special issue: Discrete mathematics & data mining II (DM & DM II)
The Gaston Tool for Frequent Subgraph Mining
Electronic Notes in Theoretical Computer Science (ENTCS)
Pattern discovery from graph-structured data: a data mining perspective
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Discovery of frequent graph patterns that consist of the vertices with the complex structures
MCD'07 Proceedings of the 3rd ECML/PKDD international conference on Mining complex data
Efficient algorithms for mining frequent and closed patterns from semi-structured data
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Mining correlated subgraphs in graph databases
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Frequent subgraph discovery in dynamic networks
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Frequent subgraph mining in outerplanar graphs
Data Mining and Knowledge Discovery
Technical Section: Automatic discovery of common design structures in CAD models
Computers and Graphics
Fraud detection in play-money prediction markets
Information Systems and e-Business Management
On triangulation-based dense neighborhood graph discovery
Proceedings of the VLDB Endowment
Mining frequent subgraphs to extract communication patterns in data-centres
ICDCN'11 Proceedings of the 12th international conference on Distributed computing and networking
Proceedings of the 14th International Conference on Extending Database Technology
Learning graph prototypes for shape recognition
Computer Vision and Image Understanding
Computing graph-based lattices from smallest projections
KONT'07/KPP'07 Proceedings of the First international conference on Knowledge processing and data analysis
CP-index: on the efficient indexing of large graphs
Proceedings of the 20th ACM international conference on Information and knowledge management
Implicit enumeration of patterns
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
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PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
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CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Graph clustering based on structural similarity of fragments
Proceedings of the 2005 international conference on Federation over the Web
Frequency concepts and pattern detection for the analysis of motifs in networks
Transactions on Computational Systems Biology III
Cl-GBI: a novel approach for extracting typical patterns from graph-structured data
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An algorithm for network motif discovery in biological networks
International Journal of Data Mining and Bioinformatics
Learning closed sets of labeled graphs for chemical applications
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Extracting discriminative patterns from graph structured data using constrained search
PKAW'06 Proceedings of the 9th Pacific Rim Knowledge Acquisition international conference on Advances in Knowledge Acquisition and Management
What can we do with graph-structured data? – a data mining perspective
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
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DBSec'12 Proceedings of the 26th Annual IFIP WG 11.3 conference on Data and Applications Security and Privacy
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Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
A General Framework for Mining Frequent Subgraphs from Labeled Graphs
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Graph-based Relational Learning with Application to Security
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Constructing a Decision Tree for Graph-Structured Data and its Applications
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
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International Journal of Data Warehousing and Mining
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OO-FSG: an object-oriented approach to mine frequent subgraphs
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Basket Analysis, which is a standard method for data mining, derives frequent itemsets from database. However, its mining ability is limited to transaction data consisting of items. In reality, there are many applications where data are described in a more structural way, e.g. chemical compounds and Web browsing history. There are a few approaches that can discover characteristic patterns from graph-structured data in the field of machine learning. However, almost all of them are not suitable for such applications that require a complete search for all frequent subgraph patterns in the data. In this paper, we propose a novel principle and its algorithm that derive the characteristic patterns which frequently appear in graph-structured data. Our algorithm can derive all frequent induced subgraphs from both directed and undirected graph structured data having loops (including self-loops) with labeled or unlabeled nodes and links. Its performance is evaluated through the applications to Web browsing pattern analysis and chemical carcinogenesis analysis.