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» Graph Mining based on a Data Partitioning Approach
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132
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DATAMINE
2006
230views more  DATAMINE 2006»
15 years 21 days ago
Mining top-K frequent itemsets from data streams
Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu
92
Voted
PAKDD
2005
ACM
133views Data Mining» more  PAKDD 2005»
15 years 6 months ago
An Anomaly Detection Method for Spacecraft Using Relevance Vector Learning
This paper proposes a novel anomaly detection system for spacecrafts based on data mining techniques. It constructs a nonlinear probabilistic model w.r.t. behavior of a spacecraft ...
Ryohei Fujimaki, Takehisa Yairi, Kazuo Machida
110
Voted
IJCNN
2006
IEEE
15 years 6 months ago
Prototype based outlier detection
— Outliers refer to “minority” data that are different from most other data. They usually disturb data mining process. But, sometimes they provide valuable information. Thus,...
Seungtaek Kim, Sungzoon Cho
103
Voted
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
16 years 1 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
RIVF
2003
15 years 2 months ago
Airspace Sectorization By Constraint Programming
—In this paper we consider the Airspace Sectorization Problem (ASP) where airspace has to be partitioned into a number of sectors, each sector being assigned to a team of air tra...
Huy Trandac, Philippe Baptiste, Vu Duong