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Recommender systems in e-commerce

Open access
Schafer, J. Ben, Konstan, Joseph, Riedl, John·1999·Proceedings of the 1st ACM conference on Electronic commerce

Abstract

Recommender systems are changing from novelties used by a few E-commerce sites, to serious business tools that are re-shaping the world of E-commerce.Many of the largest commerce Web sites are already using recommender systems to help their customers find products to purchase.A recommender system learns from a customer and recommends products that she will find most valuable from among the available products.In this paper we present an explanation of how recommender systems help Ecommerce sites increase sales, and analyze six sites that use recommender systems including several sites that use more than one recommender system.Based on the examples, we create a taxonomy of recommender systems, including the interfaces they present to customers, the technologies used to create the recommendations, and the inputs they need from customers.We conclude with ideas for new applications of recommender systems to E-commerce.

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Metadata

Authors
Schafer, J. B., Konstan, J., & Riedl, J.
Venue
Proceedings of the 1st ACM conference on Electronic commerce
Publisher
ACM
Published
1999-11
Pages
158-166
OpenAlex
W1997136459
Cited by
1,684
References
0
FWCI
27.43
Type
conference paper
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Recommender systems in e-commerce. https://app.cochat.ai/papers/10.1145/336992.337035
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Schafer, J. B., Konstan, J., & Riedl, J. (1999). Recommender systems in e-commerce. Proceedings of the 1st ACM conference on Electronic commerce. https://doi.org/10.1145/336992.337035

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.