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ISNN
2011
Springer
12 years 11 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
IJCNN
2006
IEEE
14 years 2 months ago
Prototype based outlier detection
— Outliers refer to “minority” data that are different from most other data. They usually disturb data mining process. But, sometimes they provide valuable information. Thus,...
Seungtaek Kim, Sungzoon Cho
CIKM
2008
Springer
13 years 11 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
BMCBI
2008
220views more  BMCBI 2008»
13 years 9 months ago
Gene prediction in metagenomic fragments: A large scale machine learning approach
Background: Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. ...
Katharina J. Hoff, Maike Tech, Thomas Lingner, Rol...
JSS
2010
198views more  JSS 2010»
13 years 3 months ago
Accelerated collection of sensor data by mobility-enabled topology ranks
We study the problem of fast and energy-efficient data collection of sensory data using a mobile sink, in wireless sensor networks in which both the sensors and the sink move. Mot...
Constantinos Marios Angelopoulos, Sotiris E. Nikol...