کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10322212 | 660850 | 2015 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A general methodology for n-dimensional trajectory clustering
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Trajectory data is rich in dimensionality, often containing valuable patterns in more than just the spatial and temporal dimensions. Yet existing trajectory clustering techniques only consider a fixed number of dimensions. We propose a general trajectory clustering methodology which can detect clusters using any arbitrary number of the n-dimensions available in the data. To exemplify our methodology we apply it an existing trajectory clustering approach, TRACLUS, to create the so-called, ND-TRACLUS. Furthermore, in order to better describe the trajectory clusters uncovered when clustering arbitrary dimensions we also introduce, Retraspam, a novel algorithm for n-dimensional representative trajectory formulation. We qualitatively and quantitatively evaluate both our methodology and Retraspam using two real world datasets and find valuable, previously unknown higher dimensional trajectory patterns.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 42, Issue 21, 30 November 2015, Pages 7573-7581
Journal: Expert Systems with Applications - Volume 42, Issue 21, 30 November 2015, Pages 7573-7581
نویسندگان
Luke Bermingham, Ickjai Lee,