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DATA PROCESSING DEVICE, DATA PROCESSING METHOD, AND PROGRAM

  • US 20130197890A1
  • Filed: 11/07/2011
  • Published: 08/01/2013
  • Est. Priority Date: 11/18/2010
  • Status: Active Grant
First Claim
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1. A data processing device comprising:

  • learning means configured to obtain a parameter of a probability model when a user'"'"'s movement history data to be obtained as data for learning is represented as a probability model that represents the user'"'"'s activity;

    destination and route point estimating means configured to estimate, of state nodes of the probability model using the parameter obtained by the learning means, a destination node and a route point node equivalent to a movement destination and a route point;

    prediction data generating means configured to obtain the user'"'"'s movement history data within a predetermined period of time from the present which differs from the data for learning, as data for prediction, and in the event that there is a data missing portion included in the obtained data for prediction, to generate the data missing portion thereof by interpolation processing, and to calculate virtual error with actual data corresponding to interpolated data generated by the interpolation processing;

    current point estimating means configured to input the data for prediction of which the data missing portion has been interpolated to the probability model using the parameter obtained by learning, and with estimation of state node series corresponding to the data for prediction of which the data missing portion has been interpolated, to estimate a current point node equivalent to the user'"'"'s current location by using the virtual error as an observation probability of the state nodes regarding the interpolated data, and using an observation probability with less contribution of data than actual data;

    search means configured to search a route from the user'"'"'s current location to a destination using information regarding the estimated destination node and route point node and the current point node, and the probability model obtained by learning; and

    calculating means configured to calculate an arrival probability and time required for the searched destination.

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