Learning within-session budgets from browsing trajectories

RecSys '18: Twelfth ACM Conference on Recommender Systems Vancouver British Columbia Canada October, 2018, pp. 432-436, 2018.

Cited by: 1|Bibtex|Views118|DOI:https://doi.org/10.1145/3240323.3240401
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Other Links: dblp.uni-trier.de|academic.microsoft.com|dl.acm.org

Abstract:

Building price- and budget-aware recommender systems is critical in settings where one wishes to produce recommendations that balance users' preferences (what they like) with a model of purchase likelihood (what they will buy). A trivial solution consists of learning global budget terms for each user based on their past expenditure. To mo...More

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