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Human Curation and Convnets: Powering Item-to-Item Recommendations on Pinterest

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arxiv 1511.04003 v1 pith:2265VOUT submitted 2015-11-12 cs.CV

Human Curation and Convnets: Powering Item-to-Item Recommendations on Pinterest

Dmitry Kislyuk , Yuchen Liu , David Liu , Eric Tzeng , Yushi Jing This is my paper
classification cs.CV
keywords item-to-itemcontent-basedconvnetscurationpinterestrankingrecommendationsystem
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This paper presents Pinterest Related Pins, an item-to-item recommendation system that combines collaborative filtering with content-based ranking. We demonstrate that signals derived from user curation, the activity of users organizing content, are highly effective when used in conjunction with content-based ranking. This paper also demonstrates the effectiveness of visual features, such as image or object representations learned from convnets, in improving the user engagement rate of our item-to-item recommendation system.

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