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» Time series shapelets: a new primitive for data mining
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SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 9 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
SDM
2008
SIAM
206views Data Mining» more  SDM 2008»
13 years 9 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
AIA
2006
13 years 9 months ago
Efficient Algorithm for Calculating Similarity between Trajectories Containing an Increasing Dimension
Time series data is usually stored and processed in the form of discrete trajectories of multidimensional measurement points. In order to compare the measurements of a query traje...
Perttu Laurinen, Pekka Siirtola, Juha Röning
KDD
2001
ACM
203views Data Mining» more  KDD 2001»
14 years 8 months ago
Ensemble-index: a new approach to indexing large databases
The problem of similarity search (query-by-content) has attracted much research interest. It is a difficult problem because of the inherently high dimensionality of the data. The ...
Eamonn J. Keogh, Selina Chu, Michael J. Pazzani
BTW
2009
Springer
240views Database» more  BTW 2009»
13 years 8 months ago
Efficient Adaptive Retrieval and Mining in Large Multimedia Databases
Abstract: Multimedia databases are increasingly common in science, business, entertainment and many other applications. Their size and high dimensionality of features are major cha...
Ira Assent