Alternate data clustering for fast pattern matching in stream time series data Conference

Vishwanath, RH, Thanagamani, M, Venugopal, KR et al. (2012). Alternate data clustering for fast pattern matching in stream time series data . Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 108 LNICST 153-158. 10.1007/978-3-642-35615-5_22

cited authors

  • Vishwanath, RH; Thanagamani, M; Venugopal, KR; Iyengar, SS; Patnaik, LM

abstract

  • Stream time series retrieval has been a major area of study due to its vast application in various fields like weather forecasting, multimedia data retrieval and huge data analysis. Presently, there is a demand for stream data processing, high speed searching and quick response. In this paper, we use a alternate data cluster or segment mean method for stream time series data, where the data is pruned with a computational cost of O(log w). This approach can be used for both static and dynamic stream data processing. The results obtained are the better than the existing algorithms. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

authors

publication date

  • December 1, 2012

published in

Digital Object Identifier (DOI)

start page

  • 153

end page

  • 158

volume

  • 108 LNICST