کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
405385 | 677551 | 2008 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Discovering original motifs with different lengths from time series
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Finding previously unknown patterns in a time series has received much attention in recent years. Of the associated algorithms, the k-motif algorithm is one of the most effective and efficient. It is also widely used as a time series preprocessing routine for many other data mining tasks. However, the k-motif algorithm depends on the predefine of the parameter w, which is the length of the pattern. This paper introduces a novel k-motif-based algorithm that can solve the existing problem and, moreover, provide a way to generate the original patterns by summarizing the discovered motifs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 21, Issue 7, October 2008, Pages 666–671
Journal: Knowledge-Based Systems - Volume 21, Issue 7, October 2008, Pages 666–671
نویسندگان
Heng Tang, Stephen Shaoyi Liao,