کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
476511 | 699629 | 2011 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An extended k-means technique for clustering moving objects
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
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چکیده انگلیسی
k-means algorithm is one of the basic clustering techniques that is used in many data mining applications. In this paper we present a novel pattern based clustering algorithm that extends the k-means algorithm for clustering moving object trajectory data. The proposed algorithm uses a key feature of moving object trajectories namely, its direction as a heuristic to determine the different number of clusters for the k-means algorithm. In addition, we use the silhouette coefficient as a measure for the quality of our proposed approach. Finally, we present experimental results on both real and synthetic data that show the performance and accuracy of our proposed technique.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Egyptian Informatics Journal - Volume 12, Issue 1, March 2011, Pages 45–51
Journal: Egyptian Informatics Journal - Volume 12, Issue 1, March 2011, Pages 45–51
نویسندگان
Omnia Ossama, Hoda M.O. Mokhtar, Mohamed E. El-Sharkawi,