Density-Based Estimation of POI Boundaries Using Geo-Tagged Tweets 


Vol. 42,  No. 2, pp. 453-459, Feb.  2017


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  Abstract

Users tend to check in and post their statuses in location-based social networks (LBSNs) to describe that their interests are related to a point-of-interest (POI). While previous studies on discovering area-of-interests (AOIs) were conducted mostly on the basis of density-based clustering methods with the collection of geo-tagged photos from LBSNs, we focus on estimating a POI boundary, which corresponds to only one cluster containing its POI center. Using geo-tagged tweets recorded from Twitter users, this paper introduces a density-based low-complexity two-phase method to estimate a POI boundary by finding a suitable radius reachable from the POI center. We estimate a boundary of the POI as the convex hull of selected geo-tags through our two-phase density-based estimation, where each phase proceeds with different sizes of radius increment. It is shown that our method outperforms the conventional density-based clustering method in terms of computational complexity.

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  Cite this article

[IEEE Style]

W. Shin and D. D. Vu, "Density-Based Estimation of POI Boundaries Using Geo-Tagged Tweets," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 2, pp. 453-459, 2017. DOI: .

[ACM Style]

Won-Yong Shin and Dung D. Vu. 2017. Density-Based Estimation of POI Boundaries Using Geo-Tagged Tweets. The Journal of Korean Institute of Communications and Information Sciences, 42, 2, (2017), 453-459. DOI: .

[KICS Style]

Won-Yong Shin and Dung D. Vu, "Density-Based Estimation of POI Boundaries Using Geo-Tagged Tweets," The Journal of Korean Institute of Communications and Information Sciences, vol. 42, no. 2, pp. 453-459, 2. 2017.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880