mlsanityData to 14 Oct 2026

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

arXiv 1711.03560 ↗First posted 9 Nov 2017stat.ML cs.LG econ.EMcited by 14

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Abstract (arXiv)

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 large-scale data, and we analyze a large dataset from a major chain grocery store. We are interested in answering counterfactual queries about changes in prices. We found that SHOPPER provides accurate predictions even under price interventions, and that it helps identify complementary and substitutable pairs of products.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Nov 2017.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 5; 2023: 3; 2024: 2; 2025: 1; 2026: 2.

14 papers.

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  1. 2022CAREER: A Foundation Model for Labor Sequence Datacited by 11
  2. 2022Graph-Based Methods for Discrete Choicecited by 6
  3. 2023Transformer Choice Net: A Transformer Neural Network for Choice Predictioncited by 6
  4. 2024Advancing Retail Data Science: Comprehensive Evaluation of Synthetic Datacited by 6
  5. 2023RetailSynth: Synthetic Data Generation for Retail AI Systems Evaluationcited by 5
  6. 2025Demand Estimation with Text and Image Datacited by 2
  7. 2021Pseudo-Euclidean Attract-Repel Embeddings for Undirected Graphscited by 1
  8. 2022Identifying Substitute and Complementary Products for Assortment Optimization with Cleora Embeddingscited by 1
  9. 2022Sequence-to-Set Generative Modelscited by 1
  10. 2023Torch-Choice: A PyTorch Package for Large-Scale Choice Modeling with Pythoncited by 1
  11. 2022A Causal Approach for Business Optimization: Application on an Online Marketplacecited by 0
  12. 2024A Survey of Reasoning for Substitution Relationships: Definitions, Methods, and Directionscited by 0
2 more
  1. 2026Structured Nonparametric Variational Inference for Dependent Latent Modelingcited by 0
  2. 2026Better Capturing Interactions Between Products in~Retail: Revisited Negative Sampling for~Basket Choice Modelingcited by 0