Sequential pattern mining of geo-tagged photos with an arbitrary regions-of-interest detection method

Cai, Guochen;Hio, Chihiro;Bermingham, Luke;Lee, Kyungmi;Lee, Ickjai

Abstract

Geo-tagged photos leave trails of movement that form trajectories. Regions-of- interest detection identifies interesting hot spots where many trajectories visit and large geo-tagged photos are uploaded. Extraction of exact shapes of regions-of- interest is a key step to understanding these trajectories and mining sequential trajectory patterns. This article introduces an efficient and effective grid-based regions-of-interest detection method that is linear to the number of grid cells, and is able to detect arbitrary shapes of regions-of-interest. The proposed algorithm is combined with sequential pattern mining to reveal sequential trajectory patterns. Experimental results reveal quality regions-of-interest and promising sequential trajectory patterns that demonstrate the benefits of our algorithm.

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Expert Systems with Applications

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0957-4174

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Elsevier

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DOI

10.1016/j.eswa.2013.10.057