Low-complexity detection of POI boundaries using geo-tagged Tweets: A geographic proximity based approach

Dung D. Vu, Won Yong Shin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Users tend to check in and post their statuses in location- based social networks (LBSNs) to describe that their in- Terests are related to a point-of-interest (POI). Since the relevance of the data to the POI varies according to the ge- ographic distance between the POI and the locations where the data are generated, it is important to characterize an area-of-interest (AOI) that enables to utilize the location information in a variety of businesses, services, and place advertisements. While previous studies on discovering AOIs were conducted based mostly on density-based clustering methods with the collection of geo-tagged photos from LB- SNs, we focus on detecting 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 low-complexity two-phase strategy to detect a POI boundary by finding a suitable radius reachable from the POI center. We detect a polygon-type boundary of the POI as the convex hull (i.e., the outermost region) of selected geo-tags through our two-phase approach, where each phase proceeds on with different sizes of radius increment, thus yielding a more precise boundary. It is shown that our approach outperforms the conventional density-based clustering method in terms of runtime complexity.

Original languageEnglish
Title of host publicationProceedings of the 8th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2015 - Held in Conjunction with ACM SIGSPATIAL 2015
EditorsSen Xu, Alexei Pozdnoukhov, Dimitris Sacharidis
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450339759
DOIs
Publication statusPublished - 2015 Nov 3
Event8th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2015 - Seattle, United States
Duration: 2015 Nov 32015 Nov 6

Publication series

NameProceedings of the 8th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2015 - Held in Conjunction with ACM SIGSPATIAL 2015

Conference

Conference8th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2015
CountryUnited States
CitySeattle
Period15/11/315/11/6

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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    Vu, D. D., & Shin, W. Y. (2015). Low-complexity detection of POI boundaries using geo-tagged Tweets: A geographic proximity based approach. In S. Xu, A. Pozdnoukhov, & D. Sacharidis (Eds.), Proceedings of the 8th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2015 - Held in Conjunction with ACM SIGSPATIAL 2015 [a5] (Proceedings of the 8th ACM SIGSPATIAL International Workshop on Location-Based Social Networks, LBSN 2015 - Held in Conjunction with ACM SIGSPATIAL 2015). Association for Computing Machinery, Inc. https://doi.org/10.1145/2830657.2830663