A Survey on Clustering Density Based Data Stream algorithms

  • Authors

    • Mayas Aljibawi
    • Mohd Zakree Ahmed Nazri
    • Zalinda Othman
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.36.23735
  • data mining, clustering, density-based clustering, grid-based clustering, micro-clustering, stream data clustering.

  • With the rapid evolution of technology, data size has increased as well. Thus, open the door to a new challenge of finding patterns such as the limitation of memory and time and the one pass to the whole data. Many clustering techniques has been developed to overcome these issues. Streaming data evolve with time, and that makes it almost impossible to define clusters number in that data. Density-based algorithm is one of the significant data clustering class to overcome this issue due to it doesn’t require an advance knowledge about the number of clusters. This paper reviewed some of the existing density-based clustering algorithms for the data stream with the measurement used to evaluate the algorithm.

     


     

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    Aljibawi, M., Zakree Ahmed Nazri, M., & Othman, Z. (2018). A Survey on Clustering Density Based Data Stream algorithms. International Journal of Engineering & Technology, 7(4.36), 147-153. https://doi.org/10.14419/ijet.v7i4.36.23735