@inbook {717,
	title = {Clustering Time Series Data: An Evolutionary Approach },
	booktitle = {Foundations of Computational Intelligence, Volume 206, pp.193-207},
	year = {2008},
	publisher = {Springer },
	organization = {Springer },
	abstract = {<p>Time series clustering is an important topic, particularly for similarity search amongst long time series such as those arising in bioinformatics, in marketing research, software engineering and management. This chapter discusses the state-of-the-art methodology for some mining time series databases and presents a new evolutionary algorithm for times series clustering an input time series data set. The data mining methods presented include techniques for efficient segmentation, indexing, and clustering time series. </p>
},
	url = {http://www.springerlink.com/content/a543578042r75456/},
	author = {Aboul Ella Hassanien}
}
