Incremental clustering of data stream using real ants behavior
Nesrine Masmoudi, Hanane Azzag, Mustapha Lebbah, Cyrille Bertelle · 2014
We present in this paper a new biomimetic method nammed CL-AntInc for data incremental clustering. This algorithm uses the behavior of real ants. We deal with the issue of data volume through a clustering heuristic. Dynamic graphs are constructed according to a simulation of colonial odors and pheromone mechanisms. We used numerical databases extracted from the Machine Learning Repository. The experimental results show the effectiveness of the suggested algorithm.