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» Unsupervised Clustering In Streaming Data
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ESANN
2004
14 years 11 months ago
Fast semi-automatic segmentation algorithm for Self-Organizing Maps
Self-Organizing Maps (SOM) are very powerful tools for data mining, in particular for visualizing the distribution of the data in very highdimensional data sets. Moreover, the 2D m...
David Opolon, Fabien Moutarde
KDD
2009
ACM
217views Data Mining» more  KDD 2009»
15 years 10 months ago
Efficient anomaly monitoring over moving object trajectory streams
Lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. This problem is challengin...
Yingyi Bu, Lei Chen 0002, Ada Wai-Chee Fu, Dawei L...
COMAD
2009
14 years 11 months ago
Categorizing Concepts for Detecting Drifts in Stream
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
Sharanjit Kaur, Vasudha Bhatnagar, Sameep Mehta, S...
ICANN
2007
Springer
15 years 4 months ago
Visualising Class Distribution on Self-organising Maps
The Self-Organising Map is a popular unsupervised neural network model which has been used successfully in various contexts for clustering data. Even though labelled data is not re...
Rudolf Mayer, Taha Abdel Aziz, Andreas Rauber
SISAP
2008
IEEE
147views Data Mining» more  SISAP 2008»
15 years 4 months ago
An Empirical Evaluation of a Distributed Clustering-Based Index for Metric Space Databases
Similarity search has been proved suitable for searching in very large collections of unstructured data objects. We are interested in efficient parallel query processing under si...
Veronica Gil Costa, Mauricio Marín, Nora Re...