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Dynamic based stream clustering using ants
Data stream mining is the process of extracting knowledge from continuous sequences of data. It differs from conventional data mining in that a stream is potentially unbounded, data points arrive online and each data point ...
Finding multi-density clusters in non-stationary data streams using an ant colony with adaptive parameters
(IEEE Press, 2017-06)
Density based methods have been shown to be an effective approach for clustering non-stationary data streams. The number of clusters does not need to be known a priori and density methods are robust to noise and changes ...
Ant colony stream clustering: A fast density clustering algorithm for dynamic data streams
(IEEE Press, 2018-03-30)
A data stream is a continuously arriving sequence of data and clustering data streams requires additional considerations to traditional clustering. A stream is potentially unbounded, data points arrive on-line and each ...