Marrying Top-k with Skyline Queries: Operators with Relaxed Preference Input and Controllable Output Size
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 ow...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2024
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| Online Access: | https://ink.library.smu.edu.sg/sis_research/9706 https://ink.library.smu.edu.sg/context/sis_research/article/10706/viewcontent/TODS25.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
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