Telescope

Zooming to interesting skylines

Jongwuk Lee, Gae Won You, Seungwon Hwang

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

13 Citations (Scopus)

Abstract

As data of an unprecedented scale are becoming accessible, skyline queries have been actively studied lately, to retrieve "interesting" data objects that are not dominated by any other objects, i.e., skyline objects. When the dataset is high-dimensional, however, such skyline objects are often too numerous to identify truly interesting objects. This paper studies the "curse of dimensionality" problem in skyline queries. That is, our work complements existing research efforts to address this "curse of dimensionality", by ranking skyline objects based on user-specific qualitative preference. In particular, Algorithm Telescope abstracts skyline ranking as a dynamic search over skyline subspaces guided by user-specific preference with correctness and optimality guarantees. Our extensive evaluation results validate the effectiveness and efficiency of Algorithm Telescope on both real-life and synthetic data.

Original languageEnglish
Title of host publicationAdvances in Databases
Subtitle of host publicationConcepts, Systems and Applications - 12th International Conference on Database Systems for Advanced Applications, DASFAA 2007, Proceedings
Pages539-550
Number of pages12
Publication statusPublished - 2007 Dec 1
Event12th International Conference on Database Systems for Advanced Applications, DASFAA 2007 - Bangkok, Thailand
Duration: 2007 Apr 92007 Apr 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4443 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Database Systems for Advanced Applications, DASFAA 2007
CountryThailand
CityBangkok
Period07/4/907/4/12

Fingerprint

Skyline
Telescopes
Telescope
Curse of Dimensionality
Ranking
Query
Synthetic Data
Object
Correctness
Optimality
High-dimensional
Complement
Subspace
Evaluation

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Lee, J., You, G. W., & Hwang, S. (2007). Telescope: Zooming to interesting skylines. In Advances in Databases: Concepts, Systems and Applications - 12th International Conference on Database Systems for Advanced Applications, DASFAA 2007, Proceedings (pp. 539-550). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4443 LNCS).
Lee, Jongwuk ; You, Gae Won ; Hwang, Seungwon. / Telescope : Zooming to interesting skylines. Advances in Databases: Concepts, Systems and Applications - 12th International Conference on Database Systems for Advanced Applications, DASFAA 2007, Proceedings. 2007. pp. 539-550 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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title = "Telescope: Zooming to interesting skylines",
abstract = "As data of an unprecedented scale are becoming accessible, skyline queries have been actively studied lately, to retrieve {"}interesting{"} data objects that are not dominated by any other objects, i.e., skyline objects. When the dataset is high-dimensional, however, such skyline objects are often too numerous to identify truly interesting objects. This paper studies the {"}curse of dimensionality{"} problem in skyline queries. That is, our work complements existing research efforts to address this {"}curse of dimensionality{"}, by ranking skyline objects based on user-specific qualitative preference. In particular, Algorithm Telescope abstracts skyline ranking as a dynamic search over skyline subspaces guided by user-specific preference with correctness and optimality guarantees. Our extensive evaluation results validate the effectiveness and efficiency of Algorithm Telescope on both real-life and synthetic data.",
author = "Jongwuk Lee and You, {Gae Won} and Seungwon Hwang",
year = "2007",
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Lee, J, You, GW & Hwang, S 2007, Telescope: Zooming to interesting skylines. in Advances in Databases: Concepts, Systems and Applications - 12th International Conference on Database Systems for Advanced Applications, DASFAA 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4443 LNCS, pp. 539-550, 12th International Conference on Database Systems for Advanced Applications, DASFAA 2007, Bangkok, Thailand, 07/4/9.

Telescope : Zooming to interesting skylines. / Lee, Jongwuk; You, Gae Won; Hwang, Seungwon.

Advances in Databases: Concepts, Systems and Applications - 12th International Conference on Database Systems for Advanced Applications, DASFAA 2007, Proceedings. 2007. p. 539-550 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4443 LNCS).

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

TY - GEN

T1 - Telescope

T2 - Zooming to interesting skylines

AU - Lee, Jongwuk

AU - You, Gae Won

AU - Hwang, Seungwon

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AB - As data of an unprecedented scale are becoming accessible, skyline queries have been actively studied lately, to retrieve "interesting" data objects that are not dominated by any other objects, i.e., skyline objects. When the dataset is high-dimensional, however, such skyline objects are often too numerous to identify truly interesting objects. This paper studies the "curse of dimensionality" problem in skyline queries. That is, our work complements existing research efforts to address this "curse of dimensionality", by ranking skyline objects based on user-specific qualitative preference. In particular, Algorithm Telescope abstracts skyline ranking as a dynamic search over skyline subspaces guided by user-specific preference with correctness and optimality guarantees. Our extensive evaluation results validate the effectiveness and efficiency of Algorithm Telescope on both real-life and synthetic data.

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M3 - Conference contribution

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Lee J, You GW, Hwang S. Telescope: Zooming to interesting skylines. In Advances in Databases: Concepts, Systems and Applications - 12th International Conference on Database Systems for Advanced Applications, DASFAA 2007, Proceedings. 2007. p. 539-550. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).