ZOZO研究所が実施する「検索/推薦技術に関する論文読み会」 - ZOZO TECH BLOG
こんにちは。ZOZO研究所の山﨑です。 ZOZO研究所では、検索/推薦技術をメインテーマとした論文読み会を進めてきました。週に1回の頻度で発表担当者が読んできた論文の内容を共有し、その内容を参加者で議論します。 本記事では、その会で発表された論文のサマリーを紹介します。 目次 目次 検索/推薦技術に関する論文読み会 発表論文とその概要 SIGIR [SIGIR 2005] Relevance Weighting for Query Independent Evidence [SIGIR 2010] Temporal Diversity in Recommender System [SIGIR 2017] On Application of Learning to Rank for E-Commerce Search [SIGIR 2018] Should I Follow the Crow
Learning a unified embedding for visual search at Pinterest | the morning paper
the morning paper a random walk through Computer Science research, by Adrian Colyer Made delightfully fast by strattic Learning a unified embedding for visual search at Pinterest Zhai et al., KDD’19 Last time out we looked at some great lessons from Airbnb as they introduced deep learning into their search system. Today’s paper choice highlights an organisation that has been deploying multiple dee
Learning a Unified Embedding for Visual Search at Pinterest
At Pinterest, we utilize image embeddings throughout our search and recommendation systems to help our users navigate through visual content by powering experiences like browsing of related content and searching for exact products for shopping. In this work we describe a multi-task deep metric learning system to learn a single unified image embedding which can be used to power our multiple visual
Searching for Apparel Products from Images in the Wild
In this age of social media, people often look at what others are wearing. In particular, Instagram and Twitter influencers often provide images of themselves wearing different outfits and their followers are often inspired to buy similar clothes.We propose a system to automatically find the closest visually similar clothes in the online Catalog (street-to-shop searching). The problem is challengi
Visual Search at Pinterest
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 powe
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Building a Large-scale, Accurate and Fresh Knowledge Graph
Learning to Rank Broad and Narrow Queries in E-Commerce
Seven Tips for Visual Search at Scale
