NDLI: Region sampling and estimation of geosocial data with dynamic range calibration

Content Provider	IEEE Xplore Digital Library
Author	Yanhua Li Steiner, M. Jie Bao Limin Wang Ting Zhu
Copyright Year	2014
Description	Author affiliation: Akamai Inc., CA, USA (Steiner, M.) \|\| Univ. of Minnesota, Minneapolis, MN, USA (Jie Bao) \|\| Bell Labs., Murray, NJ, USA (Limin Wang) \|\| Binghamton Univ., Binghamton, NY, USA (Ting Zhu) \|\| HUAWEI Noah's Ark Lab., China (Yanhua Li)
Abstract	Location based social networks (LBSNs) are becoming increasingly popular with the fast deployment of broadband mobile networks and the growing prevalence of versatile mobile devices. This success has attracted great interest in studying and measuring the characteristics of LBSNs, such as Facebook Places, Yelp, and Google+ Local. However, it is often prohibitive, and sometimes too costly, to obtain a detailed and complete snapshot of a LBSN due to its usually massive scale. In this work, taking Foursquare as an example, we focus on sampling and estimating restricted geographic regions in LBSNs, such as a city or a country. By exploiting the application programming interfaces (APIs) provided by Foursquare for geographic search, we first introduce how to obtain the “ground truth”, namely, a complete set of all venues (i.e., places) in a specified region. Then, we propose random region sampling algorithms that allow us to draw representative samples of venues, and design unbiased estimators of regional characteristics of venues. We validate the efficiency of our sampling algorithms on Foursquare using complete datasets obtained from 12 regions, such as Switzerland, New York City and Los Angeles. Our results are applicable to perform sampling and estimation in all GeoDatabases, such as Facebook Places, Yelp, and Google+ Local, which have similar venue search APIs as Foursquare. These location service providers can also benefit from our results to enable efficient online statistic estimation.
Sponsorship	IEEE Comput. Soc.
Starting Page	1096
Ending Page	1107
File Size	2189775
Page Count	12
File Format	PDF
ISBN	9781479925551
DOI	10.1109/ICDE.2014.6816726
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Estimation Algorithm design and analysis Cities and towns Clustering algorithms Educational institutions Facebook
Content Type	Text
Resource Type	Article

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