SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements

arXiv: Machine Learning, Volume abs/1711.03560, 2017.

Cited by: 5|Views28
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Abstract:

We develop SHOPPER, a sequential probabilistic model of shopping data. SHOPPER uses interpretable components to model the forces that drive how a customer chooses products; in particular, we designed SHOPPER to capture how items interact with other items. We develop an efficient posterior inference algorithm to estimate these forces from ...More

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