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» Numbers in Multi-relational Data Mining
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AIR
2000
91views more  AIR 2000»
13 years 8 months ago
PlanMine: Predicting Plan Failures Using Sequence Mining
This paper presents the PLANMINE sequence mining algorithm to extract patterns of events that predict failures in databases of plan executions. New techniques were needed because p...
Mohammed Javeed Zaki, Neal Lesh, Mitsunori Ogihara
KAIS
2008
150views more  KAIS 2008»
13 years 8 months ago
A survey on algorithms for mining frequent itemsets over data streams
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
James Cheng, Yiping Ke, Wilfred Ng
ASUNAM
2011
IEEE
12 years 8 months ago
MultiAspectForensics: Pattern Mining on Large-Scale Heterogeneous Networks with Tensor Analysis
—Modern applications such as web knowledge base, network traffic monitoring and online social networks have made available an unprecedented amount of network data with rich type...
Koji Maruhashi, Fan Guo, Christos Faloutsos
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 8 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
198views Data Mining» more  KDD 2006»
14 years 8 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald