• DOI:10.1145/3328526.3329642
Corpus ID: 85529625

Identifying Bid Leakage in Procurement Auctions: Machine Learning Approach

@article{Ivanov2019IdentifyingBL,
  title={Identifying Bid Leakage in Procurement Auctions: Machine Learning Approach},
  author={Dmitry Ivanov and Alexander S. Nesterov},
  journal={Proceedings of the 2019 ACM Conference on Economics and Computation},
  year={2019}
}

Dmitry Ivanov, Alexander S. Nesterov

Published 2019

Computer Science

Proceedings of the 2019 ACM Conference on Economics and Computation

We propose a novel machine-learning-based approach to detect bid leakage in first-price sealed-bid auctions. We extract and analyze the data on more than 1.4 million Russian procurement auctions between 2014 and 2018. As bid leakage in each particular auction is tacit, the direct classification is impossible. Instead, we reduce the problem of bid leakage detection to Positive-Unlabeled Classification. The key idea is to regard the losing participants as fair and the winners as possibly… CONTINUE READING

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