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Issue No.05 - May (2013 vol.12)
pp: 945-956
Choonoh Lee , Korea Advanced Institute of Science and Technology
Giwan Yoon , Korea Advanced Institute of Science and Technology
Dongsoo Han , Korea Advanced Institute of Science and Technology
Research on place extraction has been of interest for the detection of meaningful places that users visit. Because interpretations of meaningful places may be different according to location-based applications, a universal place extraction algorithm that is able to detect all kinds of meaningful places needs to be developed. Unfortunately, most previously proposed place extraction algorithms failed to show high place detection accuracy and also failed to perfectly detect meaningful places. In this work, we propose a new place extraction algorithm that can significantly enhance the accuracy of place extraction. The basic concept of the proposed algorithm is a superstate model, which is an extension of the Hidden Markov Model (HMM); we substituted superstates for the simple probabilistic distributions of the HMM. Our proposed algorithm shows remarkable detection accuracy in place extraction, significantly higher than any other previously proposed algorithms. Furthermore, the proposed algorithm can efficiently operate in mobile environments because its computations are simple.
Clustering algorithms, Hidden Markov models, Global Positioning System, Accuracy, Algorithm design and analysis, Probabilistic logic, Vectors, place extraction, Location dependent and sensitive, pervasive computing
Choonoh Lee, Giwan Yoon, Dongsoo Han, "A Probabilistic Place Extraction Algorithm Based on a Superstate Model", IEEE Transactions on Mobile Computing, vol.12, no. 5, pp. 945-956, May 2013, doi:10.1109/TMC.2012.64
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