@article{(Open Science Index):https://publications.waset.org/pdf/3359,
	  title     = {A New History Based Method to Handle the Recurring Concept Shifts in Data Streams},
	  author    = {Hossein Morshedlou and  Ahmad Abdollahzade Barforoush},
	  country	= {},
	  institution	= {},
	  abstract     = {Recent developments in storage technology and
networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate
decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is
logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among
concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data
streams.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {3},
	  number    = {10},
	  year      = {2009},
	  pages     = {2459 - 2464},
	  ee        = {https://publications.waset.org/pdf/3359},
	  url   	= {https://publications.waset.org/vol/34},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 34, 2009},
	}