Third International conference on advances in communication, network and computing

Research Article

Alternate Data Clustering for Fast Pattern Matching in Stream Time Series Data

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  • @INPROCEEDINGS{10.1007/978-3-642-35615-5_22,
        author={Vishwanath R.H. and Thanagamani M. and Venugopal K.R. and Iyengar S.S. and L. Patnaik},
        title={Alternate Data Clustering for Fast Pattern Matching in Stream Time Series Data},
        proceedings={Third International conference on advances in communication, network and computing},
        proceedings_a={CNC},
        year={2012},
        month={12},
        keywords={Stream time series Alternate data clustering Fast pattern match Cluster mean},
        doi={10.1007/978-3-642-35615-5_22}
    }
    
  • Vishwanath R.H.
    Thanagamani M.
    Venugopal K.R.
    Iyengar S.S.
    L. Patnaik
    Year: 2012
    Alternate Data Clustering for Fast Pattern Matching in Stream Time Series Data
    CNC
    Springer
    DOI: 10.1007/978-3-642-35615-5_22
Vishwanath R.H.1,*, Thanagamani M.1, Venugopal K.R.1, Iyengar S.S.2, L. Patnaik3
  • 1: Bangalore University
  • 2: Florida International University
  • 3: Indian Institute of Science
*Contact email: vishwanath_hulipalled@rediffmail.com

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 ). This approach can be used for both static and dynamic stream data processing. The results obtained are the better than the existing algorithms.