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» Approximate data mining in very large relational data
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SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
15 years 11 months ago
Top-k Correlative Graph Mining.
Correlation mining has been widely studied due to its ability for discovering the underlying occurrence dependency between objects. However, correlation mining in graph databases ...
Yiping Ke, James Cheng, Jeffrey Xu Yu
KDD
2004
ACM
147views Data Mining» more  KDD 2004»
15 years 7 months ago
Clustering time series from ARMA models with clipped data
Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering...
Anthony J. Bagnall, Gareth J. Janacek
SIGMOD
2007
ACM
192views Database» more  SIGMOD 2007»
16 years 1 months ago
Benchmarking declarative approximate selection predicates
Declarative data quality has been an active research topic. The fundamental principle behind a declarative approach to data quality is the use of declarative statements to realize...
Amit Chandel, Oktie Hassanzadeh, Nick Koudas, Moha...
GD
2006
Springer
15 years 5 months ago
Controllable and Progressive Edge Clustering for Large Networks
Node-link diagrams are widely used in information visualization to show relationships among data. However, when the size of data becomes very large, node-link diagrams will become ...
Huamin Qu, Hong Zhou, Yingcai Wu
BMCBI
2008
141views more  BMCBI 2008»
15 years 1 months ago
Ontology-guided data preparation for discovering genotype-phenotype relationships
Complexity of post-genomic data and multiplicity of mining strategies are two limits to Knowledge Discovery in Databases (KDD) in life sciences. Because they provide a semantic fr...
Adrien Coulet, Malika Smaïl-Tabbone, Pascale ...