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BMCBI
2008
208views more  BMCBI 2008»
13 years 8 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...

Publication
344views
12 years 6 months ago
Top-k Similarity Join over Multi-valued Objects
The top-k similarity joins have been extensively studied and used in a wide spectrum of applications such as information retrieval, decision making, spatial data analysis and dat...
Wenjie Zhang, Jing Xu, Xin Liang, Ying Zhang, Xuem...
KDD
2002
ACM
140views Data Mining» more  KDD 2002»
14 years 8 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han
SDM
2008
SIAM
120views Data Mining» more  SDM 2008»
13 years 9 months ago
Spatial Scan Statistics for Graph Clustering
In this paper, we present a measure associated with detection and inference of statistically anomalous clusters of a graph based on the likelihood test of observed and expected ed...
Bei Wang, Jeff M. Phillips, Robert Schreiber, Denn...
KDD
2009
ACM
196views Data Mining» more  KDD 2009»
14 years 2 months ago
WhereNext: a location predictor on trajectory pattern mining
The pervasiveness of mobile devices and location based services is leading to an increasing volume of mobility data. This side effect provides the opportunity for innovative meth...
Anna Monreale, Fabio Pinelli, Roberto Trasarti, Fo...