• DocumentCode
    3739377
  • Title

    Cross-Device Tracking: Matching Devices and Cookies

  • Author

    D?az-Morales

  • Author_Institution
    IDI Dept., Treelogic, Llanera, Spain
  • fYear
    2015
  • Firstpage
    1699
  • Lastpage
    1704
  • Abstract
    The number of computers, tablets and smartphones is increasing rapidly, which entails the ownership and use of multiple devices to perform online tasks. As people move across devices to complete these tasks, their identities becomes fragmented. Understanding the usage and transition between those devices is essential to develop efficient applications in a multi-device world. In this paper we present a solution to deal with the cross-device identification of users based on semi-supervised machine learning methods to identify which cookies belong to an individual using a device. The method proposed in this paper scored third in the ICDM 2015 Drawbridge Cross-Device Connections challenge proving its good performance.
  • Keywords
    "IP networks","Training","Electronic mail","Computers","Performance evaluation","Prediction algorithms","Supervised learning"
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshop (ICDMW), 2015 IEEE International Conference on
  • Electronic_ISBN
    2375-9259
  • Type

    conf

  • DOI
    10.1109/ICDMW.2015.244
  • Filename
    7395891