June 11, 2024, 4:47 a.m. | Jason Shuo Zhang, Benjamin Howson, Panayiota Savva, Eleanor Loh

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.06433v1 Announce Type: new
Abstract: Personalised discount codes provide a powerful mechanism for managing customer relationships and operational spend in e-commerce. Bandits are well suited for this product area, given the partial information nature of the problem, as well as the need for adaptation to the changing business environment. Here, we introduce DISCO, an end-to-end contextual bandit framework for personalised discount code allocation at ASOS.com. DISCO adapts the traditional Thompson Sampling algorithm by integrating it within an integer program, thereby …

abstract arxiv business commerce cs.ai cs.lg customer customer relationships e-commerce environment framework information nature personalised problem product relationships spend type

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