Predicting Auction Price of Vehicle License Plate with Deep Residual Learning

Vinci Chow

Abstract: Due to superstition, license plates with desirable combinations of characters are highly sought after in China, fetching prices that can reach into the millions in government-held auctions. Despite the high stakes involved, there has been essentially no attempt to provide price estimates for license plates. We present an end-to-end neural network model that simultaneously predict the auction price, gives the distribution of prices and produces latent feature vectors. While both types of neural network architectures we consider outperform simpler machine learning methods, convolutional networks outperform recurrent networks for comparable training time or model complexity. The resulting model powers our online price estimator and search engine.

Date: 2019-10
New Economics Papers: this item is included in nep-big, nep-cmp, nep-for and nep-tre
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Published in Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2019. Lecture Notes in Computer Science, vol 11607. Springer, Cham

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1910.04879

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