A new online clustering approach for data in arbitrary shaped clusters

@article{Hyde2015ANO,
  title={A new online clustering approach for data in arbitrary shaped clusters},
  author={Richard Hyde and Plamen P. Angelov},
  journal={2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)},
  year={2015},
  pages={228-233}
}
In this paper we demonstrate a new density based clustering technique, CODSAS, for online clustering of streaming data into arbitrary shaped clusters. CODAS is a two stage process using a simple local density to initiate micro-clusters which are then combined into clusters. Memory efficiency is gained by not storing or re-using any data. Computational efficiency is gained by using hyper-spherical micro-clusters to achieve a micro-cluster joining technique that is dimensionally independent for… CONTINUE READING
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