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DATAMINE
2000
118views more  DATAMINE 2000»
13 years 7 months ago
Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support
Abstract: Spatial data mining algorithms heavily depend on the efficient processing of neighborhood relations since the neighbors of many objects have to be investigated in a singl...
Martin Ester, Alexander Frommelt, Hans-Peter Krieg...
KDD
2005
ACM
151views Data Mining» more  KDD 2005»
14 years 8 months ago
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has man...
Qiaozhu Mei, ChengXiang Zhai
HPCC
2005
Springer
14 years 1 months ago
High Performance Subgraph Mining in Molecular Compounds
Structured data represented in the form of graphs arises in several fields of the science and the growing amount of available data makes distributed graph mining techniques partic...
Giuseppe Di Fatta, Michael R. Berthold
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 8 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
AUSDM
2007
Springer
193views Data Mining» more  AUSDM 2007»
14 years 1 months ago
Are Zero-suppressed Binary Decision Diagrams Good for Mining Frequent Patterns in High Dimensional Datasets?
Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-di...
Elsa Loekito, James Bailey