Scalable Algorithm for Subsequence Similarity Search in Very Large Time Series Data on Cluster of Phi KNL

2019 ◽  
pp. 149-164 ◽  
Author(s):  
Yana Kraeva ◽  
Mikhail Zymbler
Keyword(s):  
Time Series ◽  
Similarity Search ◽  
Large Time ◽  
Time Series Data ◽  
Series Data ◽  
Scalable Algorithm

Trend-Based Similarity Search in Time-Series Data

2010 ◽  
Author(s):  
Martin Suntinger ◽  
Hannes Obweger ◽  
Josef Schiefer ◽  
Philip Limbeck ◽  
Günther Raidl
Keyword(s):  
Time Series ◽  
Similarity Search ◽  
Time Series Data ◽  
Series Data

A Method for the Detection of Planetary Transits in Large Time Series Data Sets

2005 ◽  
Vol 620 (2) ◽  
pp. 1033-1042 ◽  
Author(s):  
David T. F. Weldrake ◽  
Penny D. Sackett
Keyword(s):  
Time Series ◽  
Large Time ◽  
Time Series Data ◽  
Series Data ◽  
Data Sets ◽  
Planetary Transits

scholarly journals AN OVERVIEW OF SIMILARITY SEARCH IN TIME SERIES DATA

2011 ◽  
Vol 14 (2) ◽  
pp. 71-79
Author(s):  
Anh Tuan Duong
Keyword(s):  
Time Series ◽  
Large Time ◽  
Time Series Data ◽  
Query Sequence ◽  
Real Life ◽  
Series Data ◽  
Science And Engineering ◽  
Access Methods ◽  
The Common ◽  
Spatial Access Methods

Time series data occur in many real life applications, ranging from science and engineering to business. In many of these applications, searching through large time series database based on query sequence is often desirable. Such similarity-based retrieval is also the basic subroutine in several advanced time series data mining tasks such as clustering, classification, finding motifs, detecting anomaly patterns, rule discovery and visualization. Although several different approaches have been developed, most are based on the common premise of dimensionality reduction and spatial access methods. This survey gives an overview of recent research and shows how the methods fit into a general framework of feature extraction.

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