• DocumentCode
    3673526
  • Title

    Lossy Compression of Dynamic, Weighted Graphs

  • Author

    Wilko Henecka;Matthew Roughan

  • Author_Institution
    Sch. of Math. Sci., Univ. of Adelaide, Adelaide, SA, Australia
  • fYear
    2015
  • Firstpage
    427
  • Lastpage
    434
  • Abstract
    A graph is used to represent data in which the relationships between the objects in the data are at least as important as the objects themselves. Large graph datasets are becoming more common as networks such as the Internet grow, and our ability to measure these graphs improves. This necessitates methods to compress these datasets. In this paper we present a method aimed at lossy compression of large, dynamic, weighted graphs.
  • Keywords
    "Approximation methods","Approximation algorithms","Weight measurement","Heuristic algorithms","Social network services","Noise"
  • Publisher
    ieee
  • Conference_Titel
    Future Internet of Things and Cloud (FiCloud), 2015 3rd International Conference on
  • Type

    conf

  • DOI
    10.1109/FiCloud.2015.64
  • Filename
    7300849
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3673526