On evaluating social proximity-aware spatial range queries

Yuhan Sun, Nitin Pasumarthy, Mohamed Elsayed

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

3 Scopus citations

Abstract

Spatial range queries are used on a daily basis in real-life applications, such as Google Maps and Yelp. Many of those applications may need to rank the spatial objects, enclosed by the spatial range, before presenting the result to the end-user. Existing systems rank spatial objects according to different rules, such as average user rating, distance to the user's location, etc.. The popularity of social networks allowed many applications to leverage the social graph in delivering a social-proximity aware ranked list of spatial objects. In this paper, we formally define a query that returns the top-k spatial objects in a given spatial region and rank them according to the social proximity of these objects to the querying user (SKNNGEO). Furthermore, a framework that integrates a joint search on both the social and spatial domains is proposed to efficiently solve the SKNNGEO query. The paper evaluates the proposed approach using real dataset extracted from the Yelp application. Extensive experiments show that the proposed approach outperform existing baseline approaches in processing SKNNGEO query.

Original languageEnglish (US)
Title of host publicationProceedings - 18th IEEE International Conference on Mobile Data Management, MDM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages72-81
Number of pages10
ISBN (Electronic)9781538639320
DOIs
StatePublished - Jun 29 2017
Event18th IEEE International Conference on Mobile Data Management, MDM 2017 - Daejeon, Korea, Republic of
Duration: May 29 2017Jun 1 2017

Other

Other18th IEEE International Conference on Mobile Data Management, MDM 2017
CountryKorea, Republic of
CityDaejeon
Period5/29/176/1/17

Keywords

  • GeoSocial Graph
  • Social Proximity
  • Spatial Range Query

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications
  • Information Systems and Management

Fingerprint Dive into the research topics of 'On evaluating social proximity-aware spatial range queries'. Together they form a unique fingerprint.

  • Cite this

    Sun, Y., Pasumarthy, N., & Elsayed, M. (2017). On evaluating social proximity-aware spatial range queries. In Proceedings - 18th IEEE International Conference on Mobile Data Management, MDM 2017 (pp. 72-81). [7962438] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MDM.2017.20