• DocumentCode
    3576289
  • Title

    A New Method for Link Prediction Using Various Features in Social Networks

  • Author

    Zhang Yu ; Gao Kening ; Li Feng ; Yu Ge

  • Author_Institution
    Comput. Center, Northeastern Univ., Shenyang, China
  • fYear
    2014
  • Firstpage
    144
  • Lastpage
    147
  • Abstract
    Link prediction is a basic problem in the research of social networks. At present, most link prediction algorithms are based on the features extracted from network structure, few research concerns the effect of natural attributes of nodes for creating a link. In this paper we develop a novel way to predict links based on Random Walk algorithm using the information from both the network topology and rich node attributes. The experiment result show that our method can help improves the prediction accuracy and it proves that node attributes have a real effect on link creation.
  • Keywords
    feature extraction; social networking (online); topology; features extraction; link prediction; network structure; network topology; random walk algorithm; social networks; Educational institutions; Feature extraction; Indexes; Network topology; Prediction algorithms; Social network services; Training; Random Walk; link prediction; node attribute; social network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Information System and Application Conference (WISA), 2014 11th
  • Print_ISBN
    978-1-4799-5726-2
  • Type

    conf

  • DOI
    10.1109/WISA.2014.34
  • Filename
    7058003