Reverse ranking query over imprecise spatial data

Ken C.K. Lee, Mao Ye, Wang Chien Lee

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

2 Scopus citations

Abstract

The reverse rank of a (data) object o with respect to a given query object q (that measures the relative nearness of q to o) is said to be κ when q is the κ-th nearest neighbor of o in a geographical space. Based on the notion of reverse ranks, a Reverse Ranking (RR) query determines t objects with the smallest κ's with respect to a given query object q. In many situations that locations of objects and a query object can be imprecise, objects would receive multiple possible κ's. In this paper, we propose a notion of expected reverse ranks and evaluation of RR queries over imprecise data based on expected reverse ranks. For any object o, an expected reverse rank κ̄ is a weighted average of possible reverse ranks for individual instances of o with respect to different instances of a given query object q by taking their probabilities into account. We devise and present incremental κ̄ computation and two κ̄-Estimating algorithms to efficiently evaluate RR queries over imprecise data. The efficiency of our approach is demonstrated through experiments.

Original languageEnglish (US)
Title of host publicationCOM.Geo 2010 - 1st International Conference and Exhibition on Computing for Geospatial Research and Application
DOIs
StatePublished - Aug 6 2010
Event1st International Conference and Exhibition on Computing for Geospatial Research and Application, COM.Geo 2010 - Washington, DC, United States
Duration: Jun 21 2010Jun 23 2010

Publication series

NameACM International Conference Proceeding Series

Other

Other1st International Conference and Exhibition on Computing for Geospatial Research and Application, COM.Geo 2010
Country/TerritoryUnited States
CityWashington, DC
Period6/21/106/23/10

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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