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TKDE
2008
156views more  TKDE 2008»
13 years 7 months ago
A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets
Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, mining spatio-temporal sequential patterns ident...
Yan Huang, Liqin Zhang, Pusheng Zhang
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 8 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
KDD
2005
ACM
205views Data Mining» more  KDD 2005»
14 years 26 days ago
Feature bagging for outlier detection
Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel feature bagging approach for detecting outliers in...
Aleksandar Lazarevic, Vipin Kumar
KDD
2010
ACM
300views Data Mining» more  KDD 2010»
13 years 5 months ago
Using data mining techniques to address critical information exchange needs in disaster affected public-private networks
Crisis Management and Disaster Recovery have gained immense importance in the wake of recent man and nature inflicted calamities. A critical problem in a crisis situation is how t...
Li Zheng, Chao Shen, Liang Tang, Tao Li, Steven Lu...
SSD
2005
Springer
173views Database» more  SSD 2005»
14 years 26 days 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