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KDD
2003
ACM
192views Data Mining» more  KDD 2003»
16 years 7 days ago
Efficient elastic burst detection in data streams
Burst detection is the activity of finding abnormal aggregates in data streams. Such aggregates are based on sliding windows over data streams. In some applications, we want to mo...
Yunyue Zhu, Dennis Shasha
PAKDD
2010
ACM
212views Data Mining» more  PAKDD 2010»
15 years 4 months ago
Fast Perceptron Decision Tree Learning from Evolving Data Streams
Abstract. Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffdi...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
WISE
2005
Springer
15 years 5 months ago
A Web Recommendation Technique Based on Probabilistic Latent Semantic Analysis
Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of clickstream data will lead to capture usag...
Guandong Xu, Yanchun Zhang, Xiaofang Zhou
PKDD
2009
Springer
149views Data Mining» more  PKDD 2009»
15 years 6 months ago
Learning to Disambiguate Search Queries from Short Sessions
Web searches tend to be short and ambiguous. It is therefore not surprising that Web query disambiguation is an actively researched topic. To provide a personalized experience for ...
Lilyana Mihalkova, Raymond J. Mooney
SDM
2009
SIAM
343views Data Mining» more  SDM 2009»
15 years 9 months ago
Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation.
Change-point detection is the problem of discovering time points at which properties of time-series data change. This covers a broad range of real-world problems and has been acti...
Masashi Sugiyama, Yoshinobu Kawahara