Publication Type
Journal Article
Version
publishedVersion
Publication Date
1-2025
Abstract
The two most common paradigms to identify records of preference in a multi-objective setting rely either on dominance (e.g., the skyline operator) or on a utility function defined over the records' attributes (typically, using a top-k query). Despite their proliferation, each of them has its own palpable drawbacks. Motivated by these drawbacks, we identify three hard requirements for practical decision support, namely, personalization, controllable output size, and flexibility in preference specification. With these requirements as a guide, we combine elements from both paradigms and propose two new operators, ORD and ORU. We perform a qualitative study to demonstrate how they work, and evaluate their performance against adaptations of previous work that mimic their output.
Keywords
Top-k query, skyline, multi-dimensional datasets
Discipline
Computer Sciences | Databases and Information Systems
Research Areas
Data Science and Engineering
Areas of Excellence
Digital transformation
Publication
ACM Transactions on Database Systems
Volume
50
Issue
1
First Page
1
Last Page
37
ISSN
0362-5915
Identifier
10.1145/3705726
Publisher
Association for Computing Machinery (ACM)
Citation
MOURATIDIS, Kyriakos; LI, Keming; and TANG, Bo.
Marrying top-k with skyline queries: Operators with relaxed preference input and controllable output size. (2025). ACM Transactions on Database Systems. 50, (1), 1-37.
Available at: https://ink.library.smu.edu.sg/sis_research/9706
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.1145/3705726