Design of a User Location Prediction Algorithm Using the Flexible Window Scheme 


Vol. 32,  No. 6, pp. 550-557, Jun.  2007


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  Abstract

We predict a context of various structures by using Bayesian Networks Algorithms, Three-Dimensional Structures Algorithms and Genetic Algorithms. However, these algorithms have unavoidable problems when providing a context-aware service in reality due to a lack of practicality and the delay of process time in real-time environment. As far as context-aware system for specific purpose is concerned, it is very hard to be sure about the accuracy and reliability of prediction. This paper focuses on reasoning and prediction technology which provides a stochastic mechanism for context information by incorporating various context information data. The objective of this paper is to provide optimum services to users by suggesting an intellectual reasoning and prediction based on hierarchical context information. Thus, we propose a design of user location prediction algorithm using sequential matching with n-size flexible window scheme by taking user's habit or behavior into consideration. This algorithm improves average 5.10% than traditional algorithms in the accuracy and reliability of prediction using the Flexible Window Scheme.

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  Cite this article

[IEEE Style]

B. Son, Y. Kim, E. Nahm, H. Kim, "Design of a User Location Prediction Algorithm Using the Flexible Window Scheme," The Journal of Korean Institute of Communications and Information Sciences, vol. 32, no. 6, pp. 550-557, 2007. DOI: .

[ACM Style]

Byounghee Son, Yonghoon Kim, Euiseok Nahm, and Hagbae Kim. 2007. Design of a User Location Prediction Algorithm Using the Flexible Window Scheme. The Journal of Korean Institute of Communications and Information Sciences, 32, 6, (2007), 550-557. DOI: .

[KICS Style]

Byounghee Son, Yonghoon Kim, Euiseok Nahm, Hagbae Kim, "Design of a User Location Prediction Algorithm Using the Flexible Window Scheme," The Journal of Korean Institute of Communications and Information Sciences, vol. 32, no. 6, pp. 550-557, 6. 2007.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880