Spatial skyline queries: An efficient geometric algorithm

Wanbin Son, Mu Woong Lee, Hee Kap Ahn, Seung Won Hwang

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

25 Citations (Scopus)

Abstract

As more data-intensive applications emerge, advanced retrieval semantics, such as ranking and skylines, have attracted attention. Geographic information systems are such an application with massive spatial data. Our goal is to efficiently support skyline queries over massive spatial data. To achieve this goal, we first observe that the best known algorithm VS 2, despite its claim, may fail to deliver correct results. In contrast, we present a simple and efficient algorithm that computes the correct results. To validate the effectiveness and efficiency of our algorithm, we provide an extensive empirical comparison of our algorithm and VS 2 in several aspects.

Original languageEnglish
Title of host publicationAdvances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings
Pages247-264
Number of pages18
DOIs
Publication statusPublished - 2009 Nov 2
Event11th International Symposium on Spatial and Temporal Databases, SSTD 2009 - Aalborg, Denmark
Duration: 2009 Jul 82009 Jul 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5644 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Symposium on Spatial and Temporal Databases, SSTD 2009
CountryDenmark
CityAalborg
Period09/7/809/7/10

Fingerprint

Skyline
Geometric Algorithms
Efficient Algorithms
Spatial Data
Query
Geographic Information Systems
Ranking
Retrieval
Geographic information systems
Semantics

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Son, W., Lee, M. W., Ahn, H. K., & Hwang, S. W. (2009). Spatial skyline queries: An efficient geometric algorithm. In Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings (pp. 247-264). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5644 LNCS). https://doi.org/10.1007/978-3-642-02982-0_17
Son, Wanbin ; Lee, Mu Woong ; Ahn, Hee Kap ; Hwang, Seung Won. / Spatial skyline queries : An efficient geometric algorithm. Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings. 2009. pp. 247-264 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Son, W, Lee, MW, Ahn, HK & Hwang, SW 2009, Spatial skyline queries: An efficient geometric algorithm. in Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5644 LNCS, pp. 247-264, 11th International Symposium on Spatial and Temporal Databases, SSTD 2009, Aalborg, Denmark, 09/7/8. https://doi.org/10.1007/978-3-642-02982-0_17

Spatial skyline queries : An efficient geometric algorithm. / Son, Wanbin; Lee, Mu Woong; Ahn, Hee Kap; Hwang, Seung Won.

Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings. 2009. p. 247-264 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5644 LNCS).

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

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Son W, Lee MW, Ahn HK, Hwang SW. Spatial skyline queries: An efficient geometric algorithm. In Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings. 2009. p. 247-264. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-02982-0_17