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Average Pattern and Trial-error Learning Method in Context-aware Home System

  • Journal of Knowledge Information Technology and Systems
  • Abbr : JKITS
  • 2016, 11(3), pp.279-286
  • Publisher : Korea Knowledge Information Technology Society
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Published : June 30, 2016

Byounghee Son 1 HWANG SU CHEOL 1

1인하공업전문대학

Accredited

ABSTRACT

In this paper, we propose a context-aware system to predict one’s location in behavior patterns of users. If a new behavior pattern is entered, the system runs a perceptual learning process. While running, the system uses the past three statuses and the current status information and obtains a relationship with the link. The relationship is an average pattern, which is stored and referred in a database system. The proposed system predicts the top four patterns having a high weight value among the average patterns. We suggest an algorithm by making an average pattern and using the trial-error learning method. The system offers a suitable service by considering user’s characteristics and recognizing user’s average pattern in context-aware environments. However, this paper uses just the user’s location data. Even though the system uses the average patterns and trial-error learning for the various variables of context information, the real-time response will be stable and rapid. The proposed scheme has a tendency for the accuracy of prediction to gradually enhance getting the average patterns to increase and the trial-error learning times to decrease. This algorithm will improve the accuracy and reliability of prediction for the incremental context information by incorporating various context information data and provide optimum services to users by suggesting an intellectual reasoning and prediction method based on hierarchical context information.

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