• DocumentCode
    2505629
  • Title

    Attribute fusion in a latent process model for time series of graphs

  • Author

    Priebe, Carey E. ; Lee, Nam H. ; Park, Youngser ; Tang, Minh

  • Author_Institution
    Dept. of Appl. Math. & Stat., Johns Hopkins Univ., Baltimore, MD, USA
  • fYear
    2011
  • fDate
    28-30 June 2011
  • Firstpage
    513
  • Lastpage
    516
  • Abstract
    We consider anomaly/change point detection given a time series of graphs with categorical attributes on the edges. Various attributed graph invariants are considered, and their power for detection as a function of a linear fusion parameter is presented.
  • Keywords
    graph theory; time series; attribute fusion; attributed graph invariants; latent process model; linear fusion parameter; time series; Approximation methods; Computational modeling; Data models; Mathematical model; Monte Carlo methods; Social network services; Time series analysis; Anomaly Detection; Attributed Random Graphs; Fusion; Random Dot Product Graphs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing Workshop (SSP), 2011 IEEE
  • Conference_Location
    Nice
  • ISSN
    pending
  • Print_ISBN
    978-1-4577-0569-4
  • Type

    conf

  • DOI
    10.1109/SSP.2011.5967746
  • Filename
    5967746
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2505629