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110
Voted
SDM
2008
SIAM
206views Data Mining» more  SDM 2008»
15 years 1 months ago
Latent Variable Mining with Its Applications to Anomalous Behavior Detection
In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
Shunsuke Hirose, Kenji Yamanishi
84
Voted
AUSDM
2006
Springer
136views Data Mining» more  AUSDM 2006»
15 years 4 months ago
Data Mining in Conceptualising Active Ageing
The concept of older adults contributing to society in a meaningful way has been termed `active ageing'. We present applications of data mining techniques on the active agein...
Richi Nayak, Laurie Buys, Jan Lovie-Kitchin
ICDE
2008
IEEE
136views Database» more  ICDE 2008»
16 years 1 months ago
T-Time: Threshold-Based Data Mining on Time Series
Mining time series data is an important approach for the analysis in many application areas as diverse as biology, environmental research, medicine, or stock chart analysis. As nea...
Alexey Pryakhin, Hans-Peter Kriegel, Johannes A&sz...
SDM
2007
SIAM
147views Data Mining» more  SDM 2007»
15 years 1 months ago
Constraint-Based Pattern Set Mining
Local pattern mining algorithms generate sets of patterns, which are typically not directly useful and have to be further processed before actual application or interpretation. Ra...
Luc De Raedt, Albrecht Zimmermann
ICAI
2009
14 years 10 months ago
Data Mining in Incomplete Numerical and Categorical Data Sets: A Neuro Fuzzy Approach
- There are many applications dealing with incomplete data sets that take different approaches to making imputations for missing values. Most tackle the problem for numerical input...
Pilar Rey del Castillo, Jesus Cardenosa