Mr. George Ignatius Profile

George Ignatius

at Etsy Inc

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Proceedings Article | 3 October 2024 Presentation + Paper

Evergreen missions: modeling long term user interests in e-commerce

Ravi Bhadauria, Tommy Chen, Nadia Sharma, Noa Bendit-Shtull, Mark White, George Ignatius, Karl Ni

Proceedings Volume 13138, 131380Q (2024) https://doi.org/10.1117/12.3028492

KEYWORDS: Expectation maximization algorithms, Machine learning, Systems modeling, Mixtures

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Identifying long term user interests, i.e., “evergreen missions”, in retail and e-commerce is a challenging yet important problem. In this work, we propose a machine learning system that is able to identify a user’s long term arbitrary interests by leveraging their site interaction history. Our contribution is a system that is composed of three components (1) projecting our listing inventory to an embedding space with a combination of supervised/unsupervised modeling, (2) inferring personalized interests from the embedding space to a user base with attributed interactions, and (3) estimating the repeat interaction rate with inventory through a rigorous statistical approach. Additionally, we provide novel insights by leveraging the supervised neural network model to produce a clustering approach for interest discovery. The approach has been implemented, validated, and rigorously A/B experimented with and is currently in production at Etsy, Inc., powering its several modules.

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