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Generating Top-k Packages via Preference Elicitation

Summary: Models preferences over packages with a learnable linear utility under uncertainty, updated via preference elicitation from user feedback. Offers sampling-based learning and an efficient top-k package generator with multiple ranking semantics, addressing hard constraints and Pareto overload. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11079
Venue
VLDB
Year
2014
Pagerank
5.093636e-05
Overall Rank
12,206 | 16.26%
DOI
10.14778/2733085.2733087

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BibTeX Citation

@article{xie_vldb14,
        title = {{Generating Top-k Packages via Preference Elicitation}},
        author = {Xie, Min and Lakshmanan, Laks V.S. and Wood, Peter T.},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {14},
        pages = {1941--1952},
        doi = {10.14778/2733085.2733087},
        url = {https://doi.org/10.14778/2733085.2733087},
        year = {2014}
}

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