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KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 7 months ago
Systematic data selection to mine concept-drifting data streams
One major problem of existing methods to mine data streams is that it makes ad hoc choices to combine most recent data with some amount of old data to search the new hypothesis. T...
Wei Fan
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 7 months ago
V-Miner: using enhanced parallel coordinates to mine product design and test data
Analyzing data to find trends, correlations, and stable patterns is an important task in many industrial applications. This paper proposes a new technique based on parallel coordi...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...
KDD
2003
ACM
156views Data Mining» more  KDD 2003»
16 years 7 months ago
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Defining outliers by their distance to neighboring examples is a popular approach to finding unusual examples in a data set. Recently, much work has been conducted with the goal o...
Stephen D. Bay, Mark Schwabacher
142
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KDD
2003
ACM
113views Data Mining» more  KDD 2003»
16 years 7 months ago
Mining unexpected rules by pushing user dynamics
Unexpected rules are interesting because they are either previously unknown or deviate from what prior user knowledge would suggest. In this paper, we study three important issues...
Ke Wang, Yuelong Jiang, Laks V. S. Lakshmanan
KDD
2002
ACM
128views Data Mining» more  KDD 2002»
16 years 7 months ago
Privacy preserving mining of association rules
We present a framework for mining association rules from transactions consisting of categorical items where the data has been randomized to preserve privacy of individual transact...
Alexandre V. Evfimievski, Ramakrishnan Srikant, Ra...