• DocumentCode
    1660130
  • Title

    Expertise Prediction for Social Network Platforms to Encourage Knowledge Sharing

  • Author

    Raj, Nidhi ; Dey, Lipika ; Gaonkar, Bhakti

  • Author_Institution
    TCS Innovation Labs. Delhi, Delhi, India
  • Volume
    1
  • fYear
    2011
  • Firstpage
    380
  • Lastpage
    383
  • Abstract
    Knowledge sharing social platforms where users mutually benefit through question-answering are gaining popularity. The success of these platforms on the web has led to their adoption within the firewalls of enterprises also. In this paper we have presented some in-depth study about two such platforms -- one open on the web and one which is within an enterprise to identify the similarities and dissimilarities of user behavior in the two platforms. We have proposed an algorithm to predict experts to improve the effectiveness of such platforms.
  • Keywords
    authorisation; knowledge management; question answering (information retrieval); social networking (online); firewalls; knowledge sharing social platform; question-answering; social network; user behavior; Communities; Conferences; Correlation; Data mining; Knowledge engineering; Social network services; Uninterruptible power systems; Attrition rate; Expertise prediction; Hubs; Propensity to answer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
  • Conference_Location
    Lyon
  • Print_ISBN
    978-1-4577-1373-6
  • Electronic_ISBN
    978-0-7695-4513-4
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2011.93
  • Filename
    6040743