research-article

T-LevelIndex: Towards Efficient Query Processing in Continuous Preference Space

Authors:

Keming LiAuthors Info & Claims

SIGMOD '22: Proceedings of the 2022 International Conference on Management of Data

Pages 2149 - 2162

https://doi.org/10.1145/3514221.3526182

Published: 11 June 2022 Publication History

Abstract

Top-k related queries in continuous preference space (e.g., k-shortlist preference query kSPR, uncertain top-k query UTK, output-size specified utility-based query ORU) have numerous applications but are expensive to process. Existing algorithms process each query via specialized optimizations, which are difficult to generalize. In this work, we propose a novel and general index structure T-LevelIndex, which can be used to process various queries in continuous preference space efficiently. We devise efficient approaches to build the T-LevelIndex by fully exploiting the properties of continuous preference space. We conduct extensive experimental studies on both real- and synthetic- benchmarks. The results show that (i) our proposed index building approaches have low costs in terms of both space and time, and (ii) T-LevelIndex significantly outperforms specialized solutions for processing a spectrum of queries in continuous preference space, and the speedup can be two to three orders of magnitude.

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Cited By

Wang WWong RJagadish HXie M(2024)Reverse Regret Query2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00314(4100-4112)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00314
Zhu RJia YYang XZheng BWang BZong C(2024)Multiple Continuous Top-K Queries Over Data Stream2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00129(1575-1588)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00129

Index Terms

T-LevelIndex: Towards Efficient Query Processing in Continuous Preference Space
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking
      1. Top-k retrieval in databases

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cover image ACM Conferences

SIGMOD '22: Proceedings of the 2022 International Conference on Management of Data

June 2022

2597 pages

ISBN:9781450392495

DOI:10.1145/3514221

General Chair:
Zachary Ives
University of Pennsylvania (USA)
,
Program Chairs:
Angela Bonifati
Lyon 1 University (France)
,
Amr El Abbadi
University of California, Santa Barbara (USA)

Copyright © 2022 ACM.

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Published: 11 June 2022

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SIGMOD/PODS '22: International Conference on Management of Data

June 12 - 17, 2022

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Cited By

Wang WWong RJagadish HXie M(2024)Reverse Regret Query2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00314(4100-4112)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00314
Zhu RJia YYang XZheng BWang BZong C(2024)Multiple Continuous Top-K Queries Over Data Stream2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00129(1575-1588)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00129

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