• DocumentCode
    3131608
  • Title

    RENC: Recursive Estimation of Node Characteristics using topological structure of complex networks

  • Author

    Sugiyama, Kouhei ; Ohsaki, Hiroyuki ; Imase, Makoto

  • Author_Institution
    Grad. Sch. of Inf. Sci. & Technol., Osaka Univ., Suita
  • fYear
    2008
  • fDate
    22-24 April 2008
  • Firstpage
    154
  • Lastpage
    159
  • Abstract
    In this paper, we propose a recursive estimation method of node characteristics called RENC (recursive estimation of node characteristics) using the topological structure of a complex networks. RENC reduces the effect of noise by recursively estimating node characteristics using the topological structure of a network. In this paper, we also propose a network generation model called LRE (linkage with relative evaluation). The network generation model LRE is for simulating a social network, in which every node is likely to make decision based on relative evaluation, so that it can reproduce several characteristics of a social network. In this paper, we evaluate the effectiveness of our recursive estimation method RENC by applying RENC to several networks generated with LRE. Consequently, we show that the estimation accuracy of node characteristics can be improved by using our recursive estimation method RENC.
  • Keywords
    decision making; recursive estimation; telecommunication network topology; complex network; decision making; linkage with relative evaluation; recursive estimation of node characteristic; social network; topological structure; Character generation; Citation analysis; Complex networks; Couplings; Electronic mail; Information retrieval; Information science; Noise reduction; Recursive estimation; Social network services;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Telecommunication Technologies, 2008. APSITT. 7th Asia-Pacific Symposium on
  • Conference_Location
    Bandos Island
  • Print_ISBN
    978-4-88552-226-0
  • Type

    conf

  • DOI
    10.1109/APSITT.2008.4653557
  • Filename
    4653557