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» Mining Very Large Databases
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113
Voted
ICDM
2003
IEEE
71views Data Mining» more  ICDM 2003»
15 years 9 months ago
Tree-structured Partitioning Based on Splitting Histograms of Distances
We propose a novel clustering algorithm that is similar in spirit to classification trees. The data is recursively split using a criterion that applies a discrete curve evolution...
Longin Jan Latecki, Rajagopal Venugopal, Marc Sobe...
ICDM
2003
IEEE
184views Data Mining» more  ICDM 2003»
15 years 9 months ago
Detecting Patterns of Change Using Enhanced Parallel Coordinates Visualization
Analyzing data to find trends, correlations, and stable patterns is an important problem for many industrial applications. In this paper, we propose a new technique based on paral...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...
INCDM
2010
Springer
159views Data Mining» more  INCDM 2010»
15 years 8 months ago
Semi-supervised Learning for False Alarm Reduction
Abstract. Intrusion Detection Systems (IDSs) which have been deployed in computer networks to detect a wide variety of attacks are suffering how to manage of a large number of tri...
Chien-Yi Chiu, Yuh-Jye Lee, Chien-Chung Chang, Wen...
131
Voted
KDD
1999
ACM
199views Data Mining» more  KDD 1999»
15 years 8 months ago
The Application of AdaBoost for Distributed, Scalable and On-Line Learning
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang
147
Voted
CIKM
2008
Springer
15 years 5 months ago
Characterizing and predicting community members from evolutionary and heterogeneous networks
Mining different types of communities from web data have attracted a lot of research efforts in recent years. However, none of the existing community mining techniques has taken i...
Qiankun Zhao, Sourav S. Bhowmick, Xin Zheng, Kai Y...