A review on time series data mining
T Fu - Engineering Applications of Artificial Intelligence, 2011 - Elsevier
Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …
scientific and financial applications. A time series is a collection of observations made …
catch22: CAnonical Time-series CHaracteristics: Selected through highly comparative time-series analysis
Capturing the dynamical properties of time series concisely as interpretable feature vectors
can enable efficient clustering and classification for time-series applications across science …
can enable efficient clustering and classification for time-series applications across science …
The move-split-merge metric for time series
A Stefan, V Athitsos, G Das - IEEE transactions on Knowledge …, 2012 - ieeexplore.ieee.org
A novel metric for time series, called Move-Split-Merge (MSM), is proposed. This metric uses
as building blocks three fundamental operations: Move, Split, and Merge, which can be …
as building blocks three fundamental operations: Move, Split, and Merge, which can be …
Multi-dimensional regression analysis of time-series data streams
Publisher Summary This chapter illustrates methods for online, multidimensional regression
analysis of time-series stream data. Real-time production systems and other dynamic …
analysis of time-series stream data. Real-time production systems and other dynamic …
Scaling and time warping in time series querying
The last few years have seen an increasing understanding that dynamic time warping
(DTW), a technique that allows local flexibility in aligning time series, is superior to the …
(DTW), a technique that allows local flexibility in aligning time series, is superior to the …
Spade: On shape-based pattern detection in streaming time series
Y Chen, MA Nascimento, BC Ooi… - 2007 IEEE 23rd …, 2006 - ieeexplore.ieee.org
Monitoring predefined patterns in streaming time series is useful to applications such as
trend-related analysis, sensor networks and video surveillance. Most current studies on such …
trend-related analysis, sensor networks and video surveillance. Most current studies on such …
Stream cube: An architecture for multi-dimensional analysis of data streams
Real-time surveillance systems, telecommunication systems, and other dynamic
environments often generate tremendous (potentially infinite) volume of stream data: the …
environments often generate tremendous (potentially infinite) volume of stream data: the …
General match: a subsequence matching method in time-series databases based on generalized windows
We generalize the method of constructing windows in subsequence matching. By this
generalization, we can explain earlier subsequence matching methods as special cases of a …
generalization, we can explain earlier subsequence matching methods as special cases of a …
Knowledge augmented machine learning with applications in autonomous driving: A survey
The availability of representative datasets is an essential prerequisite for many successful
artificial intelligence and machine learning models. However, in real life applications these …
artificial intelligence and machine learning models. However, in real life applications these …
Efficient and effective similar subtrajectory search with deep reinforcement learning
Similar trajectory search is a fundamental problem and has been well studied over the past
two decades. However, the similar subtrajectory search (SimSub) problem, aiming to return …
two decades. However, the similar subtrajectory search (SimSub) problem, aiming to return …