GeoTrend: Spatial trending queries on real-time Microblogs

Amr Magdy, Ahmed M. Aly, Mohamed F. Mokbel, Sameh Elnikety, Yuxiong He, Suman Nath, Walid G. Aref

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

7 Citations (Scopus)

Abstract

This paper presents GeoTrend; a system for scalable support of spatial trend discovery on recent microblogs, e.g., tweets and online reviews, that come in real time. GeoTrend is distinguished from existing techniques in three aspects: (1) It discovers trends in arbitrary spatial regions, e.g., city blocks. (2) It supports trending measures that effectively capture trending items under a variety of definitions that suit different applications. (3) It promotes recent microblogs as first-class citizens and optimizes its system components to digest a continuous flow of fast data in main-memory while removing old data efficiently. GeoTrend queries are top-k queries that discover the most trending k keywords that are posted within an arbitrary spatial region and during the last T time units. To support its queries efficiently, GeoTrend employs an in-memory spatial index that is able to efficiently digest incoming data and expire data that is beyond the last T time units. The index also materializes top-k keywords in different spatial regions so that incoming queries can be processed with low latency. In case of peak times, a main-memory optimization technique is employed to shed less important data, so that the system still sustains high query accuracy with limited memory resources. Experimental results based on real Twitter feed and Bing Mobile spatial search queries show the scalability of GeoTrend to support arrival rates of up to 50,000 microblog/second, average query latency of 3 milli-seconds, and at least 90+% query accuracy even under limited memory resources.

Original languageEnglish
Title of host publication24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016
EditorsMatthias Renz, Mohamed Ali, Shawn Newsam, Matthias Renz, Siva Ravada, Goce Trajcevski
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450345897
DOIs
Publication statusPublished - 31 Oct 2016
Event24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016 - Burlingame, United States
Duration: 31 Oct 20163 Nov 2016

Publication series

NameGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Other

Other24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016
CountryUnited States
CityBurlingame
Period31/10/163/11/16

    Fingerprint

Keywords

  • Indexing
  • Microblogs
  • Query Processing
  • Real-time
  • Spatial
  • Trend

ASJC Scopus subject areas

  • Earth-Surface Processes
  • Computer Science Applications
  • Modelling and Simulation
  • Computer Graphics and Computer-Aided Design
  • Information Systems

Cite this

Magdy, A., Aly, A. M., Mokbel, M. F., Elnikety, S., He, Y., Nath, S., & Aref, W. G. (2016). GeoTrend: Spatial trending queries on real-time Microblogs. In M. Renz, M. Ali, S. Newsam, M. Renz, S. Ravada, & G. Trajcevski (Eds.), 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016 [7] (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems). Association for Computing Machinery. https://doi.org/10.1145/2996913.2996986