research-article

Maximum rank query

Editors: Chen Li, Volker Markl Authors:

Kyriakos Mouratidis,

HweeHwa PangAuthors Info & Claims

Proceedings of the VLDB Endowment, Volume 8, Issue 12

Pages 1554 - 1565

https://doi.org/10.14778/2824032.2824053

Published: 01 August 2015 Publication History

Abstract

The top-k query is a common means to shortlist a number of options from a set of alternatives, based on the user's preferences. Typically, these preferences are expressed as a vector of query weights, defined over the options' attributes. The query vector implicitly associates each alternative with a numeric score, and thus imposes a ranking among them. The top-k result includes the k options with the highest scores. In this context, we define the maximum rank query (MaxRank). Given a focal option in a set of alternatives, the MaxRank problem is to compute the highest rank this option may achieve under any possible user preference, and furthermore, to report all the regions in the query vector's domain where that rank is achieved. MaxRank finds application in market impact analysis, customer profiling, targeted advertising, etc. We propose a methodology for MaxRank processing and evaluate it with experiments on real and benchmark synthetic datasets.

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Cited By

Martinenghi D(2025)Parallelizing the Computation of Grid Resistance to Measure the Strength of Skyline TuplesAlgorithms10.3390/a1801002918:1(29)Online publication date: 7-Jan-2025
https://doi.org/10.3390/a18010029
Mouratidis KLi KTang B(2024)Marrying Top-k with Skyline Queries: Operators with Relaxed Preference Input and Controllable Output SizeACM Transactions on Database Systems10.1145/370572650:1(1-37)Online publication date: 22-Nov-2024
https://dl.acm.org/doi/10.1145/3705726
Ciaccia PMartinenghi D(2024)Directional Queries: Making Top-k Queries More Effective in Discovering Relevant ResultsProceedings of the ACM on Management of Data10.1145/36988072:6(1-26)Online publication date: 20-Dec-2024
https://dl.acm.org/doi/10.1145/3698807
Show More Cited By

Maximum rank query
1. Information systems
  1. Data management systems
    1. Database management system engines
  2. Information retrieval
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory

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Information & Contributors

Information

Published In

cover image Proceedings of the VLDB Endowment

Proceedings of the VLDB Endowment Volume 8, Issue 12

Proceedings of the 41st International Conference on Very Large Data Bases, Kohala Coast, Hawaii

August 2015

728 pages

ISSN:2150-8097

Editors:
Chen Li
University of California, Irvine
,
Volker Markl
TU Berlin

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VLDB Endowment

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Published: 01 August 2015

Published in PVLDB Volume 8, Issue 12

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Cited By

Martinenghi D(2025)Parallelizing the Computation of Grid Resistance to Measure the Strength of Skyline TuplesAlgorithms10.3390/a1801002918:1(29)Online publication date: 7-Jan-2025
https://doi.org/10.3390/a18010029
Mouratidis KLi KTang B(2024)Marrying Top-k with Skyline Queries: Operators with Relaxed Preference Input and Controllable Output SizeACM Transactions on Database Systems10.1145/370572650:1(1-37)Online publication date: 22-Nov-2024
https://dl.acm.org/doi/10.1145/3705726
Ciaccia PMartinenghi D(2024)Directional Queries: Making Top-k Queries More Effective in Discovering Relevant ResultsProceedings of the ACM on Management of Data10.1145/36988072:6(1-26)Online publication date: 20-Dec-2024
https://dl.acm.org/doi/10.1145/3698807
Mouratidis K(2023)Opportunities for spatial database research in the context of preference queriesProceedings of the 7th ACM SIGSPATIAL Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising10.1145/3615896.3628418(1-3)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3615896.3628418
Zhang JTang BYiu MYan XLi KIves ZBonifati AEl Abbadi A(2022)T-LevelIndex: Towards Efficient Query Processing in Continuous Preference SpaceProceedings of the 2022 International Conference on Management of Data10.1145/3514221.3526182(2149-2162)Online publication date: 10-Jun-2022
https://dl.acm.org/doi/10.1145/3514221.3526182
Nosrati MCai Y(2022)Verifying the Correctness of Analytic Query ResultsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.303731334:9(4527-4537)Online publication date: 1-Sep-2022
https://doi.org/10.1109/TKDE.2020.3037313
Mouratidis KLi KTang BLi GLi ZIdreos SSrivastava D(2021)Marrying Top-k with Skyline Queries: Relaxing the Preference Input while Producing Output of Controllable SizeProceedings of the 2021 International Conference on Management of Data10.1145/3448016.3457299(1317-1330)Online publication date: 9-Jun-2021
https://dl.acm.org/doi/10.1145/3448016.3457299
Tang BMouratidis KHan MLi GLi ZIdreos SSrivastava D(2021)On m-Impact Regions and Standing Top-k Influence ProblemsProceedings of the 2021 International Conference on Management of Data10.1145/3448016.3452832(1784-1796)Online publication date: 9-Jun-2021
https://dl.acm.org/doi/10.1145/3448016.3452832
Nikitopoulos PSfyris GVlachou ADoulkeridis CTelelis O(2021)Pruning techniques for parallel processing of reverse top-k queriesDistributed and Parallel Databases10.1007/s10619-020-07297-939:1(169-199)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1007/s10619-020-07297-9
Ciaccia PMartinenghi D(2020)Flexible SkylinesACM Transactions on Database Systems10.1145/340611345:4(1-45)Online publication date: 10-Dec-2020
https://dl.acm.org/doi/10.1145/3406113
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