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Pinterest(中文译名:缤趣),是一个网络与手机的应用程序,可以让用户利用其平台作为个人创意及项目工作所需的视觉探索工具,同时也有人把它视为一个图片分享类的社交网站,用户可以按主题分类添加和管理自己的图片收藏,并与好友分享。其使用的网站布局为瀑布流(Pinterest-style layout)。

Pinterest由美国加州帕罗奥图的一个名为Cold Brew Labs的团队营运,创办人为Ben Silbermann、 Paul Sciarra 及 Evan Sharp。2010年正式上线。“Pinterest”是由“Pin”及“interest”两个字组成,在社交网站中的访问量仅次于Facebook、Youtube、VKontakte以及Twitter。

Manas Realtime — Enabling changes to be searchable in a blink of an eye

Manas是Pinterest内部的搜索引擎,是一个通用的信息检索平台。Manas被设计为一个具有高性能、可用性和可扩展性的搜索框架。今天,Manas为大多数Pinterest产品提供了搜索功能,包括Ads、搜索、Homefeed、Related Pins、Visual和Shopping。 搜索系统的关键指标之一是索引延迟,即更新搜索索引以反映变化所需的时间。随着系统能力的不断增强和新用例的上线,即时索引新文档的能力变得更加重要。Manas已经支持增量索引,能够提供数十分钟以内的索引延迟。不幸的是,这不能满足日益增长的来自Ads和follow feeds的业务需求。于是在Manas中构建了一个新的模块,进一步将索引延迟降低到几分之一秒。 在这篇文章中描述了系统的架构及其关键挑战,并给出了权衡的细节。

Improve user experience: solving core data inconsistencies at Pinterest

Challenges naturally occur with Pinterest’s rapid growth. As a Pinner, you might have noticed some instances where your data doesn’t look “correct,” and you may have had a negative experience because of it. For example: the “Pin count” in your profile shows the incorrect number of Pins.

Scaling Cache Infrastructure at Pinterest

Demand on Pinterest’s core infrastructure systems is accelerating faster than ever as more Pinners come to Pinterest to find inspiration. A distributed cache layer fronting many services and databases is one of our core storage systems that sits near the bottom of Pinterest’s infrastructure stack, responsible for absorbing the vast majority of backend traffic driven by this growth.

Multi-task Learning for Related Products Recommendations at Pinterest

People have always come to Pinterest for shopping inspiration, and we’ve made big strides over the years to make that as seamless as possible so Pinners (users) can go from inspiration to purchase, including evolving shoppable Product Pins, improving recommendations and making it easier for merchants to upload their catalogs to curate and feature their products.

Pinterest Visual Signals Infrastructure: Evolution from Lambda to Kappa Architecture

Ankit Patel | Software engineer, Content Acquisition and Media Platform

A better clickthrough rate: How Pinterest upgraded everyone’s favorite engagement metric

Philip Apps | Data Scientist, Ads Quality

Redesigning the Pinterest Homepage

How experimentation and cross-functional collaboration are key to making a redesign successful

How a one line change decreased our clone times by 99%

Urvashi Reddy | Software Engineer, Engineering Productivity Team Adam Berry | Tech Lead, Engineering Productivity Team Rui Li | Software…

How Pinterest runs Traffic-based Interlinking experiments for SEO

James Ouhyoung | Growth Search Traffic, Bruce Yu | Growth Search Traffic

Understanding the product cycle of discovery to purchase on Pinterest

Rui Huang, Song Cui | Software Engineers, Content Interest Understanding Team, Jennifer Zhao | Software Engineers, Content Core Signal…

Pre-Submit Integration Tests For Ads-Serving

Nishant Roy | Ads Serving

Driving Shopping Upsells from Pinterest Search

Felix Zhou | Shopping, Weiran Li | Shopping, Somnath Banerjee | Shopping

How Pinterest Supercharged its Growth Team With Experiment Idea Review

The Pinterest Growth team has over 100 members, and we’ve run thousands of experiments over the years. It’s difficult to run that many experiments and still maintain a high success rate over time. We’ve found the traditional growth team model of team leads deciding which opportunities to try didn’t scale well as our team grew. Increasing the number of high-quality ideas ready for experimentation is one of the biggest levers for increasing the impact of a growth team, but our leads have less and less time to

Pinterest推荐系统四年进化之路

四年了,从单一的推荐算法到多种推荐算法合并;从一个feature排序到几百维,上千维feature用机器排序;从2~3人的小项目到十几个人的团队,一起来看看Pinterest推荐系统都有哪些进化吧。

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