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JIPS
2010
165views more  JIPS 2010»
13 years 4 months ago
IMTAR: Incremental Mining of General Temporal Association Rules
Nowadays due to the rapid advances in the field of information systems, transactional databases are being updated regularly and/or periodically. The knowledge discovered from these...
Anour F. A. Dafa-Alla, Ho-Sun Shon, Khalid E. K. S...
IEAAIE
2009
Springer
14 years 4 months ago
Robust Singular Spectrum Transform
Change Point Discovery is a basic algorithm needed in many time series mining applications including rule discovery, motif discovery, casual analysis, etc. Several techniques for c...
Yasser F. O. Mohammad, Toyoaki Nishida
SSD
2005
Springer
173views Database» more  SSD 2005»
14 years 3 months ago
On Discovering Moving Clusters in Spatio-temporal Data
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras
ICC
2009
IEEE
132views Communications» more  ICC 2009»
14 years 4 months ago
Preprocessing DNS Log Data for Effective Data Mining
—The Domain Name Service (DNS) provides a critical function in directing Internet traffic. Defending DNS servers from bandwidth attacks is assisted by the ability to effectively...
Mark E. Snyder, Ravi Sundaram, Mayur Thakur
ADC
2007
Springer
140views Database» more  ADC 2007»
14 years 3 months ago
Incremental Mining for Temporal Association Rules for Crime Pattern Discoveries
In recent years, the concept of temporal association rule (TAR) has been introduced in order to solve the problem on handling time series by including time expressions into associ...
Vincent T. Y. Ng, Stephen Chi-fai Chan, Derek Lau,...