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» Unsupervised Outlier Detection in Time Series Data
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MICCAI
2007
Springer
14 years 8 months ago
Detection of Spatial Activation Patterns as Unsupervised Segmentation of fMRI Data
In functional connectivity analysis, networks of interest are defined based on correlation with the mean time course of a user-selected `seed' region. In this work we propose ...
Polina Golland, Yulia Golland, Rafael Malach
TKDE
2008
158views more  TKDE 2008»
13 years 7 months ago
Hierarchical Clustering of Time-Series Data Streams
This paper presents a time series whole clustering system that incrementally constructs a tree-like hierarchy of clusters, using a top-down strategy. The Online Divisive-Agglomera...
Pedro Pereira Rodrigues, João Gama, Jo&atil...
FLAIRS
2004
13 years 8 months ago
A Method Based on RBF-DDA Neural Networks for Improving Novelty Detection in Time Series
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...
ICDE
2007
IEEE
183views Database» more  ICDE 2007»
14 years 8 months ago
SpADe: On Shape-based Pattern Detection in Streaming Time Series
Monitoring predefined patterns in streaming time series is useful to applications such as trend-related analysis, sensor networks and video surveillance. Most current studies on s...
Yueguo Chen, Mario A. Nascimento, Beng Chin Ooi, A...
KDD
2000
ACM
115views Data Mining» more  KDD 2000»
13 years 11 months ago
Mining asynchronous periodic patterns in time series data
Periodicy detection in time series data is a challenging problem of great importance in many applications. Most previous work focused on mining synchronous periodic patterns and d...
Jiong Yang, Wei Wang 0010, Philip S. Yu