Time series data mining includes query by content, anomaly detection, motif discovery, predication, clustering, classification, and segmentation .
His research interests are Reinforcement learning, Time series Clustering, Financial Time series Data Mining.
This paper discussed in detail based on the actuality of the current exchange rate behavior research methods and time series data mining
, cut from the "abnormal" this new angle, using data mining method to study the RMB exchange rate behavior.
A method proposed by reference , which can find concept from time series, could be the start of the time series data mining
. Firstly, it used the property of dynamical system behind time series data to delay the time series.
One of the most challengeable clustering issues in the time series data mining
community [6-11] is time series clustering [12-18].
Time series data mining (TSDM) method [10-11] proposed in recent years combines time series analysis and data mining.
Time Series Data Mining: Identifying Temporal Patterns for Characterization and Prediction of Time Series Events.
We used five datasets (CBF, CC, Trance, Gun and Reality) from the UCR Time Series Data Mining
The experiment on the proposed model is conducted with one syntactic dataset and 12 real-word datasets obtained from the UCR Time Series Data Mining
Archive in various domains and sizes .
Fu, "A review on time series data mining
," Engineering Applications of Artificial Intelligence, vol.
Janacek, "A bit level representation for time series data mining
with shape based similarity," Data Mining and Knowledge Discovery, vol.