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KDD
2005
ACM
103views Data Mining» more  KDD 2005»
14 years 8 months ago
Fast discovery of unexpected patterns in data, relative to a Bayesian network
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Szymon Jaroszewicz, Tobias Scheffer
KDD
2004
ACM
207views Data Mining» more  KDD 2004»
14 years 8 months ago
SPIN: mining maximal frequent subgraphs from graph databases
One fundamental challenge for mining recurring subgraphs from semi-structured data sets is the overwhelming abundance of such patterns. In large graph databases, the total number ...
Jun Huan, Wei Wang 0010, Jan Prins, Jiong Yang
CHI
2007
ACM
14 years 8 months ago
Exploring patterns of social commonality among file directories at work
We studied files stored by members of a work organization for patterns of social commonality. Discovering identical or similar documents, applications, developer libraries, or oth...
John C. Tang, Clemens Drews, Mark Smith, Fei Wu, A...
SIGMOD
2003
ACM
239views Database» more  SIGMOD 2003»
14 years 8 months ago
D(k)-Index: An Adaptive Structural Summary for Graph-Structured Data
To facilitate queries over semi-structured data, various structural summaries have been proposed. Structural summaries are derived directly from the data and serve as indices for ...
Chen Qun, Andrew Lim, Kian Win Ong
EDBT
2004
ACM
119views Database» more  EDBT 2004»
14 years 7 months ago
NNH: Improving Performance of Nearest-Neighbor Searches Using Histograms
Efficient search for nearest neighbors (NN) is a fundamental problem arising in a large variety of applications of vast practical interest. In this paper we propose a novel techniq...
Liang Jin, Nick Koudas, Chen Li