• DocumentCode
    2068330
  • Title

    Evaluating Centrality Measures in Large Call Graphs

  • Author

    Kiss, Christine ; Scholz, Andreas ; Bichler, Martin

  • Author_Institution
    Internet-based Inf. Syst., Tech. Univ. Munich
  • fYear
    2006
  • fDate
    26-29 June 2006
  • Firstpage
    8
  • Lastpage
    8
  • Abstract
    Analytical methods for customer relationship management (CRM) have gained increasing importance in today´s businesses. Some industry sectors such as the telecommunication industry accumulate huge amounts of data not only about the usage behaviour of individual customers, but also about how customers interact. In addition to traditional data mining and statistical techniques, methods from the field of social network analysis (SNA) are essential to leverage this special set of data. For example, call detail records of telephone operators can be used to evaluate the network of customers and derive measures for the influence of persons in such a network. This information is relevant to viral marketing, as well as various other forms of advertising and campaign management. Research in network analysis has led to a number of different centrality measures, which are potentially useful statistics for such purposes. In this paper, we compare different centrality measures based on a variety of different network topologies and model assumptions
  • Keywords
    computer networks; customer relationship management; data mining; statistics; advertising; call detail records; campaign management; centrality measures; customer relationship management; customers interaction; data mining; large call graphs; network topologies; social network analysis; statistical techniques; telecommunication industry; telephone operators; usage behaviour; viral marketing; Advertising; Business; Communication industry; Customer relationship management; Data mining; Industrial relations; Marketing management; Social network services; Statistical analysis; Telephony;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Commerce Technology, 2006. The 8th IEEE International Conference on and Enterprise Computing, E-Commerce, and E-Services, The 3rd IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    0-7695-2511-3
  • Type

    conf

  • DOI
    10.1109/CEC-EEE.2006.44
  • Filename
    1640263