Discovering typical structures of documents: a road map approach
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Storing semistructured data with STORED
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Concurrency and Automata on Infinite Sequences
Proceedings of the 5th GI-Conference on Theoretical Computer Science
A new algorithm for the maximum-weight clique problem
Nordic Journal of Computing
Efficiently Computing Frequent Tree-Like Topology Patterns in a Web Environment
TOOLS '99 Proceedings of the 31st International Conference on Technology of Object-Oriented Language and Systems
Computing Frequent Graph Patterns from Semistructured Data
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
Preference-based configuration of web page content
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Diagonally Subgraphs Pattern Mining
Proceedings of the 9th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
SPIN: mining maximal frequent subgraphs from graph databases
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering Frequent Graph Patterns Using Disjoint Paths
IEEE Transactions on Knowledge and Data Engineering
Mining unconnected patterns in workflows
Information Systems
RDF-3X: a RISC-style engine for RDF
Proceedings of the VLDB Endowment
The RDF-3X engine for scalable management of RDF data
The VLDB Journal — The International Journal on Very Large Data Bases
Indexing and mining topological patterns for drug discovery
Proceedings of the 15th International Conference on Extending Database Technology
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Whereas data mining in structured data focuses on frequentdata values, in semi-structured and graph data theemphasis is on frequent labels and common topologies.Here, the structure of the data is just as important as itscontent.When data contains large amount of differentlabels, both fully labeled and partially data maybe useful.More informative patterns can be found in thedatabase if some of the pattern nodes can be regarded as'unlabeled'.We study the problem of discovering typicalfully and partially labeled patterns of graph data.Discovered patterns are useful in many applications, including:compact representation of source informationand a road-map for browsing and querying informationsources.