Applies Information Foraging Theory to demonstrate that visual bookmarks increase the scent of recommended images in a content-based image recommender evaluated on Pinterest.
Demystifying Core Ranking in Pinterest Image Search
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abstract
Pinterest Image Search Engine helps hundreds of millions of users discover interesting content everyday. This motivates us to improve the image search quality by evolving our ranking techniques. In this work, we share how we practically design and deploy various ranking pipelines into Pinterest image search ecosystem. Specifically, we focus on introducing our novel research and study on three aspects: training data, user/image featurization and ranking models. Extensive offline and online studies compared the performance of different models and demonstrated the efficiency and effectiveness of our final launched ranking models.
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cs.IR 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Effects of Foraging in Personalized Content-based Image Recommendation
Applies Information Foraging Theory to demonstrate that visual bookmarks increase the scent of recommended images in a content-based image recommender evaluated on Pinterest.