• DocumentCode
    3547092
  • Title

    Pathway prediction using similar users and the N-gram model

  • Author

    Kawase, Kanta ; Thawonmas, Ruck

  • Author_Institution
    Grad. Sch. of Inf. Sci. & Eng., Ritsumeikan Univ., Kusatsu, Japan
  • fYear
    2013
  • fDate
    2-4 Nov. 2013
  • Firstpage
    131
  • Lastpage
    136
  • Abstract
    This paper is about our research on user pathway prediction for being applied to a location aware system. In particular, we propose a prediction method based on an jV-gram model with Kneser-Ney smoothing (KNS), originally developed by other researchers for statistical language model smoothing, and introduce the use of the transition information of similar users into KNS. We then verify the performance of the proposed prediction method by comparing it with an existing prediction method and a prediction method based on KNS using all users´ information. The comparison result reveals that the proposed method outperforms its counterparts on all performance metrics: precision, recall, F-measure, and CA.
  • Keywords
    computational linguistics; mobile computing; prediction theory; smoothing methods; KNS; Kneser-Ney smoothing; N-gram model; location aware system; performance metrics; prediction method; statistical language model smoothing; transition information; user pathway prediction; Accuracy; Prediction algorithms; Predictive models; Probability; Smoothing methods; Training data; N-gram Model; kneser-ney smoothing; pathway prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Awareness Science and Technology and Ubi-Media Computing (iCAST-UMEDIA), 2013 International Joint Conference on
  • Conference_Location
    Aizuwakamatsu
  • Type

    conf

  • DOI
    10.1109/ICAwST.2013.6765422
  • Filename
    6765422