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A Bayesian Inference Model for Landmarks Detection on Mobile Devices  

Hwang, Keum-Sung (연세대학교 컴퓨터과학과)
Cho, Sung-Bae (연세대학교 컴퓨터과학과)
Lea, Jong-Ho (삼성종합기술원 CIL 전문연구원)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.13, no.1, 2007 , pp. 35-45 More about this Journal
Abstract
The log data collected from mobile devices contains diverse meaningful and practical personal information. However, this information is usually ignored because of its limitation of memory capacity, computation power and analysis. We propose a novel method that detects landmarks of meaningful information for users by analyzing the log data in distributed modules to overcome the problems of mobile environment. The proposed method adopts Bayesian probabilistic approach to enhance the inference accuracy under the uncertain environments. The new cooperative modularization technique divides Bayesian network into modules to compute efficiently with limited resources. Experiments with artificial data and real data indicate that the result with artificial data is amount to about 84% precision rate and about 76% recall rate, and that including partial matching with real data is about 89% hitting rate.
Keywords
mobile device log; landmark extraction model; modular Bayesian network;
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