Visual Search at Pinterest

2015/05/28 by Yushi Jing, Jing, Yushi, David Liu +11 · 2 voices · 1 citation
#cs.CV

paper · pdf · doi:10.48550/arxiv.1505.07647

Abstract

We demonstrate that, with the availability of distributed computation platforms such as Amazon Web Services and open-source tools, it is possible for a small engineering team to build, launch and maintain a cost-effective, large-scale visual search system with widely available tools. We also demonstrate, through a comprehensive set of live experiments at Pinterest, that content recommendation powered by visual search improve user engagement. By sharing our implementation details and the experiences learned from launching a commercial visual search engines from scratch, we hope visual search are more widely incorporated into today's commercial applications.

Cited by

• Deep Reinforcement Learning for Ranking Utility Tuning in the Ad Recommender System at Pinterest

Discussions

• Visual Search at Pinterest [pdf] [hn, 32 points, 7 comments]
• Visual Search at Pinterest [hn, 3 points, 0 comments]

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