Exact Primitives for Time Series Data Mining
نویسنده
چکیده
OF THE DISSERTATION Exact Primitives for Time Series Data Mining
منابع مشابه
Lag Patterns in Time Series Databases
Time series motif discovery is important as the discovered motifs generally form the primitives for many data mining tasks. In this work, we examine the problem of discovering groups of motifs from different time series that exhibit some lag relationships. We define a new class of pattern called lagPatterns that captures the invariant ordering among motifs. lagPatterns characterize localized as...
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With rapid development in information gathering technologies and access to large amounts of data, we always require methods for data analyzing and extracting useful information from large raw dataset and data mining is an important method for solving this problem. Clustering analysis as the most commonly used function of data mining, has attracted many researchers in computer science. Because o...
متن کاملExact Discovery of Time Series Motifs
Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other. As with their discrete analogues in computational biology, this similarity hints at structure which has been conserved for some reason and may therefore be of interest. Since the formalism of time series motifs in 2002, dozens of researchers have used them for d...
متن کاملAdmissible Time Series Motif Discovery with Missing Data
The discovery of time series motifs has emerged as one of the most useful primitives in time series data mining. Researchers have shown its utility for exploratory data mining, summarization, visualization, segmentation, classification, clustering, and rule discovery. Although there has been more than a decade of extensive research, there is still no technique to allow the discovery of time ser...
متن کاملPerception Based Patterns in Time Series Data Mining
Import of intelligent features to systems supporting human decisions in problems related with analysis of time series data bases is a promising research field. Such systems should be able to operate with fuzzy perception-based information about time moments and time intervals; about time series values, trends and shapes; about associations between time series and time series patterns, etc., to ...
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تاریخ انتشار 2012