  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.
