Aggregate estimations over location based services

Weimo Liu, Md Farhadur Rahman, Saravanan Thirumuruganathan, Nan Zhang, Gautam Das

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

Location based services (LBS) have become very popular in recent years. They range from map services (e.g., Google Maps) that store geographic locations of points of interests, to online social networks (e.g., WeChat, Sina Weibo, FourSquare) that leverage user geographic locations to enable various recommendation functions. The public query interfaces of these services may be abstractly modeled as a kNN interface over a database of two dimensional points on a plane: given an arbitrary query point, the system returns the k points in the database that are nearest to the query point. In this paper we consider the problem of obtaining approximate estimates of SUM and COUNT aggregates by only querying such databases via their restrictive public interfaces. We distinguish between interfaces that return location information of the returned tuples (e.g., Google Maps), and interfaces that do not return location information (e.g., SinaWeibo). For both types of interfaces, we develop aggregate estimation algorithms that are based on novel techniques for precisely computing or approximately estimating the Voronoi cell of tuples. We discuss a comprehensive set of real-world experiments for testing our algorithms, including experiments on Google Maps, WeChat, and Sina Weibo.

Original languageEnglish (US)
Title of host publicationProceedings of the VLDB Endowment
PublisherAssociation for Computing Machinery
Pages1334-1345
Number of pages12
Edition12
DOIs
StatePublished - Jan 1 2015
Event3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of
Duration: Sep 11 2006Sep 11 2006

Publication series

NameProceedings of the VLDB Endowment
Number12
Volume8
ISSN (Electronic)2150-8097

Other

Other3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006
CountryKorea, Republic of
CitySeoul
Period9/11/069/11/06

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All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Computer Science(all)

Cite this

Liu, W., Rahman, M. F., Thirumuruganathan, S., Zhang, N., & Das, G. (2015). Aggregate estimations over location based services. In Proceedings of the VLDB Endowment (12 ed., pp. 1334-1345). (Proceedings of the VLDB Endowment; Vol. 8, No. 12). Association for Computing Machinery. https://doi.org/10.14778/2824032.2824034