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» Mining data streams: a review
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SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
13 years 10 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà
SIGMOD
2007
ACM
195views Database» more  SIGMOD 2007»
14 years 9 months ago
Effective variation management for pseudo periodical streams
Many database applications require the analysis and processing of data streams. In such systems, huge amounts of data arrive rapidly and their values change over time. The variati...
Lv-an Tang, Bin Cui, Hongyan Li, Gaoshan Miao, Don...
CORR
2004
Springer
122views Education» more  CORR 2004»
13 years 8 months ago
"In vivo" spam filtering: A challenge problem for data mining
Spam, also known as Unsolicited Commercial Email (UCE), is the bane of email communication. Many data mining researchers have addressed the problem of detecting spam, generally by...
Tom Fawcett
JMLR
2010
165views more  JMLR 2010»
13 years 3 months ago
Feature Selection: An Ever Evolving Frontier in Data Mining
The rapid advance of computer technologies in data processing, collection, and storage has provided unparalleled opportunities to expand capabilities in production, services, comm...
Huan Liu, Hiroshi Motoda, Rudy Setiono, Zheng Zhao
CIKM
2007
Springer
14 years 3 months ago
Detecting distance-based outliers in streams of data
In this work a method for detecting distance-based outliers in data streams is presented. We deal with the sliding window model, where outlier queries are performed in order to de...
Fabrizio Angiulli, Fabio Fassetti