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
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;
Conference_Titel :
Awareness Science and Technology and Ubi-Media Computing (iCAST-UMEDIA), 2013 International Joint Conference on
Conference_Location :
Aizuwakamatsu
DOI :
10.1109/ICAwST.2013.6765422