Data clustering using the Bees Algorithm and the Kd-Tree structure - Al-Jabbouli, Hasan
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The most popular techniques of data clustering, which is a main task of data mining and a common technique used in many fields, are the K-means and C-means algorithms. Clustering using the K-means or C-means algorithms generally is fast and produces good results. Although these algorithms have been successfully implemented in several areas, they still have a number of limitations. The main aim of this work is to develop flexible data management strategies to address some of those limitations and improve the performance of the algorithms.

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Produktbeschreibung
The most popular techniques of data clustering, which is a main task of data mining and a common technique used in many fields, are the K-means and C-means algorithms. Clustering using the K-means or C-means algorithms generally is fast and produces good results. Although these algorithms have been successfully implemented in several areas, they still have a number of limitations. The main aim of this work is to develop flexible data management strategies to address some of those limitations and improve the performance of the algorithms.
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Autorenporträt
Dr. Hasan Al-Jabbouli has obtained his PhD. in Data Mining and Machine Learning in 2010. He is a senior lecturer in Database Systems at the School of Information Technology Engineering, Albaath University in Syria.He is the author of several articles published in reputed journals and is a member of different international working groups.