Title :
Discovering Clusters with Arbitrary Shapes and Densities in Data Streams
Author :
Magdy, Amr ; Yousri, Noha A. ; El-Makky, Nagwa M.
Author_Institution :
Comput. & Syst. Eng. Dept., Alexandria Univ., Alexandria, Egypt
Abstract :
The availability of streaming data in different fields and in various forms increases the importance of streaming data analysis. The huge size of a continuously flowing data has put forward a number of challenges in data stream analysis. Exploration of the structure of streamed data represented a major challenge that resulted in introducing various clustering algorithms. However, current clustering algorithms still lack the ability to efficiently discover clusters of arbitrary densities in data streams. In this paper, a new grid-based and density-based algorithm is proposed for clustering streaming data. It addresses drawbacks of recent algorithms in discovering clusters of arbitrary densities. The algorithm uses an online component to map the input data to grid cells. An offline component is then used to cluster the grid cells based on density information. Relative density relatedness measures and a dynamic range neighborhood are proposed to differentiate clusters of arbitrary densities. The experimental evaluation shows considerable improvements upon the state-of-the-art algorithms in both clustering quality and scalability. In addition, the output quality of the proposed algorithm is less sensitive to parameter selection errors.
Keywords :
data analysis; pattern clustering; arbitrary densities; arbitrary shapes; clustering algorithm; data stream analysis; data streams; density-based algorithm; dynamic range neighborhood; grid cells; grid-based algorithm; relative density relatedness measures; streaming data analysis; Algorithm design and analysis; Clustering algorithms; Density measurement; Heuristic algorithms; Partitioning algorithms; Scalability; Shape; Data streams mining; density-based clustering;
Conference_Titel :
Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4577-2134-2
DOI :
10.1109/ICMLA.2011.56