Browse State-of-the-Art › Context Aware Product Recommendation
Context Aware Product Recommendation
2 papers with code · 0 benchmarks · 0 datasets archive 2025-07-28
Context-aware recommender systems (CARS) generate more relevant recommendations by adapting them to the specific contextual situation of the user. This article explores how contextual information can be used to create more intelligent and useful recommender systems.
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2 shown of 2 papers with code (2 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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6 Nov 2017 2 repositories listedIn this framework, each type of information source (review text, product image, numerical rating, etc) is adopted to learn the corresponding user and item representations based on available (deep) representation…
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17 Sep 2021 1 repository listedA total of 167 participants participated in the challenge, and we secured the 6th rank during the final evaluation with an MRR of 0.
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