• DocumentCode
    1156595
  • Title

    The Clustered Causal State Algorithm: Efficient Pattern Discovery for Lossy Data-Compression Applications

  • Author

    Schmiedekamp, Mendel ; Subbu, Aparna ; Phoha, Shashi

  • Author_Institution
    Appl. Res. Lab., Penn State Univ.
  • Volume
    8
  • Issue
    5
  • fYear
    2006
  • Firstpage
    59
  • Lastpage
    67
  • Abstract
    Pattern discovery is a potential boon for data compression, but current approaches are inefficient and produce cumbersome pattern descriptions. The clustered causal state algorithm is a new pattern-discovery algorithm that incorporates recent clustering technology
  • Keywords
    data compression; data mining; pattern clustering; clustered causal state algorithm; data compression; pattern discovery; Bandwidth; Clustering algorithms; Communications technology; Costs; Data compression; Data mining; Entropy; History; Laboratories; Sensor systems and applications; clustering; model-based coding; pattern analysis; real-time systems; statistical pattern models;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCSE.2006.98
  • Filename
    1677484
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1156595