کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6862742 | 677015 | 2013 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Finding time series discord based on bit representation clustering
ترجمه فارسی عنوان
پیدا کردن اختلافات سری زمانی بر اساس خوشه بندی نمایندگی کمی
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کلمات کلیدی
داده های معدن سری زمانی، کشف اختلاف، خوشه بندی هرس کردن کاهش ابعاد،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
The problem of finding time series discord has attracted much attention recently due to its numerous applications and several algorithms have been suggested. However, most of them suffer from high computation cost and cannot satisfy the requirement of real applications. In this paper, we propose a novel discord discovery algorithm BitClusterDiscord which is based on bit representation clustering. Firstly, we use PAA (Piecewise Aggregate Approximation) bit serialization to segment time series, so as to capture the main variation characteristic of time series and avoid the influence of noise. Secondly, we present an improved K-Medoids clustering algorithm to merge several patterns with similar variation behaviors into a common cluster. Finally, based on bit representation clustering, we design two pruning strategies and propose an effective algorithm for time series discord discovery. Extensive experiments have demonstrated that the proposed approach can not only effectively find discord of time series, but also greatly improve the computational efficiency.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 54, December 2013, Pages 243-254
Journal: Knowledge-Based Systems - Volume 54, December 2013, Pages 243-254
نویسندگان
Guiling Li, Olli Bräysy, Liangxiao Jiang, Zongda Wu, Yuanzhen Wang,