کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
418016 681600 2008 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Discovering patterns in categorical time series using IFS
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Discovering patterns in categorical time series using IFS
چکیده انگلیسی

The detection of patterns in categorical time series data is an important task in many fields of science. Several efficient algorithms for finding frequent sequential patterns have been proposed. An online-approach for sequential pattern analysis based on transforming the categorical alphabet to real vectors and generating fractals by an iterated function systems (IFS) is suggested. Sequential patterns can be analyzed with standard methods of cluster analysis using this approach. A version of the procedure allows detecting patterns visually.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 52, Issue 9, 15 May 2008, Pages 4369–4379
نویسندگان
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