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BMCBI
2008
208views more  BMCBI 2008»
13 years 11 months ago
GraphFind: enhancing graph searching by low support data mining techniques
Background: Biomedical and chemical databases are large and rapidly growing in size. Graphs naturally model such kinds of data. To fully exploit the wealth of information in these...
Alfredo Ferro, Rosalba Giugno, Misael Mongiov&igra...
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 11 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 11 months ago
Identifying bridging rules between conceptual clusters
1 A bridging rule in this paper has its antecedent and action from different conceptual clusters. We first design two algorithms for mining bridging rules between clusters in a dat...
Shichao Zhang, Feng Chen, Xindong Wu, Chengqi Zhan...
PKDD
2010
Springer
152views Data Mining» more  PKDD 2010»
13 years 9 months ago
CET: A Tool for Creative Exploration of Graphs
We present a tool for interactive exploration of graphs that integrates advanced graph mining methods in an interactive visualization framework. The tool enables efficient explorat...
Stefan Haun, Andreas Nürnberger, Tobias K&oum...
ICDM
2009
IEEE
139views Data Mining» more  ICDM 2009»
13 years 8 months ago
Frequent Pattern Discovery from a Single Graph with Quantitative Itemsets
In this paper, we focus on a single graph whose vertices contain a set of quantitative attributes. Several networks can be naturally represented in this complex graph. An example i...
Yuuki Miyoshi, Tomonobu Ozaki, Takenao Ohkawa