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ICDM
2007
IEEE
175views Data Mining» more  ICDM 2007»
14 years 1 months ago
gApprox: Mining Frequent Approximate Patterns from a Massive Network
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
SIGMOD
2004
ACM
162views Database» more  SIGMOD 2004»
14 years 7 months ago
Graph Indexing: A Frequent Structure-based Approach
Graph has become increasingly important in modelling complicated structures and schemaless data such as proteins, chemical compounds, and XML documents. Given a graph query, it is...
Xifeng Yan, Philip S. Yu, Jiawei Han
JIIS
2010
106views more  JIIS 2010»
13 years 2 months ago
A new classification of datasets for frequent itemsets
The discovery of frequent patterns is a famous problem in data mining. While plenty of algorithms have been proposed during the last decade, only a few contributions have tried to ...
Frédéric Flouvat, Fabien De Marchi, ...
KDD
2006
ACM
160views Data Mining» more  KDD 2006»
14 years 7 months ago
Coherent closed quasi-clique discovery from large dense graph databases
Frequent coherent subgraphscan provide valuable knowledgeabout the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large...
Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Ka...
ACMSE
2009
ACM
14 years 2 months ago
A hybrid approach to mining frequent sequential patterns
The mining of frequent sequential patterns has been a hot and well studied area—under the broad umbrella of research known as KDD (Knowledge Discovery and Data Mining)— for we...
Erich Allen Peterson, Peiyi Tang