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DataPrice: An Interactive System for Pricing Datasets in Data Marketplaces

Summary: DataPrice is an interactive system that trains a pricing model on real commercial marketplace datasets to estimate reference prices from dataset descriptions for sellers and buyers. It leverages Shapley-value attribution over metadata attributes to generate textual explanations of price drivers, improving transparency and trust. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13864
Venue
VLDB
Year
2024
Pagerank
5.093636e-05
Overall Rank
11,325 | 22.31%
DOI
10.14778/3685800.3685893

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Authors

BibTeX Citation

@article{zhu_vldb24,
        title = {{DataPrice: An Interactive System for Pricing Datasets in Data Marketplaces}},
        author = {Zhu, Yiding and Zhang, Hongwei and Zhang, Jiayao and Liu, Jinfei and Ren, Kui},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {12},
        pages = {4433--4436},
        doi = {10.14778/3685800.3685893},
        url = {https://doi.org/10.14778/3685800.3685893},
        year = {2024}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
3,759 Dealer: An End-to-End Model Marketplace with Differential Privacy 2021 VLDB 7.14674e-05
5,191 QIRANA: A Framework for Scalable Query Pricing 2017 SIGMOD 6.3265914e-05
6,551 Efficient Sampling Approaches to Shapley Value Approximation 2023 SIGMOD 5.8429222e-05
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