Efficient continuous K-nearest neighbor query processing over moving objects with uncertain speed and direction

Yuan Ko Huang, Shi Jei Liao, Chiang Lee

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

8 Citations (Scopus)

Abstract

One of the important types of queries in spatio-temporal databases is the Continuous K-Nearest Neighbor (CKNN) query, which is to find among all moving objects the K-Nearest Neighbors (KNNs) of a mobile user at each time instant within a user-given time interval [t s , t e ]. In this paper, we focus on how to process such a CKNN query efficiently when the moving speed and direction of each moving object are uncertain. We thoroughly analyze the complicated problems incurred by this uncertainty and propose a Continuous PKNN (CPKNN) algorithm to effectively tackle these problems.

Original languageEnglish
Title of host publicationScientific and Statistical Database Management - 20th International Conference, SSDBM 2008, Proceedings
Pages549-557
Number of pages9
DOIs
Publication statusPublished - 2008 Aug 14
Event20th International Conference on Scientific and Statistical Database Management, SSDBM 2008 - Hong Kong, China
Duration: 2008 Jul 92008 Jul 11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5069 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other20th International Conference on Scientific and Statistical Database Management, SSDBM 2008
CountryChina
CityHong Kong
Period08-07-0908-07-11

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Huang, Y. K., Liao, S. J., & Lee, C. (2008). Efficient continuous K-nearest neighbor query processing over moving objects with uncertain speed and direction. In Scientific and Statistical Database Management - 20th International Conference, SSDBM 2008, Proceedings (pp. 549-557). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5069 LNCS). https://doi.org/10.1007/978-3-540-69497-7_37