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» Theoretical Frameworks for Data Mining
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PAKDD
2009
ACM
149views Data Mining» more  PAKDD 2009»
15 years 2 months ago
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data
Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection met...
Ke Zhang, Marcus Hutter, Huidong Jin
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
15 years 10 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
KDD
2002
ACM
175views Data Mining» more  KDD 2002»
15 years 10 months ago
Mining product reputations on the Web
Knowing the reputations of your own and/or competitors' products is important for marketing and customer relationship management. It is, however, very costly to collect and a...
Satoshi Morinaga, Kenji Yamanishi, Kenji Tateishi,...
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
15 years 10 months ago
Web usage mining based on probabilistic latent semantic analysis
The primary goal of Web usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of user sessions and discoveri...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
SDM
2007
SIAM
146views Data Mining» more  SDM 2007»
14 years 11 months ago
ROAM: Rule- and Motif-Based Anomaly Detection in Massive Moving Object Data Sets
With recent advances in sensory and mobile computing technology, enormous amounts of data about moving objects are being collected. One important application with such data is aut...
Xiaolei Li, Jiawei Han, Sangkyum Kim, Hector Gonza...