Graph neural networks (GNNs)
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Amazon-UCLA model wins coreference resolution challenge
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Voice-enabled devices with screens — like the Echo Show — are growing in popularity, and they offer new opportunities for multimodal interactions, in which ...

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Amazon announces new CMU graduate research fellows
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In March of 2022, Amazon and Carnegie Mellon University announced the second class of Amazon graduate research fellows, marking an expansion of the ...

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Using hypergraphs to improve product retrieval
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Information retrieval engines like the one that helps Amazon customers find products in the Amazon Store commonly rely on bipartite graphs that map queries ...

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Biased graph sampling for better related-product recommendation
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E-commerce sites often recommend products that are related to customer queries — phone cases for someone shopping for a phone, for instance. Information ...

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Can you teach a computer to smell? Osmo is trying
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At the age of 12, Alex Wiltschko bought his first perfume, Azzaro pour Homme. He’d read about it in his favorite book — Perfumes: The Guide, by Luca Turin — ...

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KDD 2023: Graph neural networks’ new frontiers
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In 2021 and 2022, when Amazon Science asked members of the program committees of the Knowledge Discovery and Data Mining Conference (KDD) to discuss the ...

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RecSys: Rajeev Rastogi on three recommendation system challenges
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Rajeev Rastogi, vice president of applied science in Amazon’s International Emerging Stores division. In a ...

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Anomaly detection for graph-based data
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Anomaly detection is the identification of data that diverges significantly from established norms, which can indicate harmful activity. It’s a particularly ...

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