Following on from their acquisition of VisualGraph last year, Pinterest are back on the machine learning acquisition hype with their latest purchase, Kosei. Kosei is machine learning startup that is led by data scientists & recommendation engine specialists.

“Over the past year, Kosei has been building a unique technology stack that drives commerce by making highly personalized and powerful product recommendations, as well as creating a system that contains more than 400 million relationships between products,” explains Michael Lopp, the head of engineering at Pinterest.

Kosei’s proprietary recommendation engine assists with greater engagement and commerce by making highly personalized and powerful product recommendations to consumers by leveraging a unique product graph that understands products and how they relate to each other.

Pinterest listed out its strategy with the newly acquired ML tool as follows:

  • The Black Ops team uses classification to detect spam content and users
  • The Discovery team (which includes search and recommendations) provides recommendations, related content, and predicts the likelihood that a person will Pin content
  • Our Visual Discovery team is working with cutting-edge deep learning algorithms to do object recognition and related object recommendations
  • The Monetization team does ad performance and relevance prediction
  • The Growth team has begun to move into the realm of using intelligence models to determine which emails to send and prevent churn
  • The Data team is building out a distributed system for machine learning using Spark, so the learning can be efficient and potentially real-time

With a data set of over 30 billion Pins and growing still Pinterest intends to upgrade the existing graph to help brands optimize the customer interaction to ‘reach people at the right moments, and improve content for Pinners.’

Read more here.


(Image credit: MKHMarketing, via Flickr)

Previous post

Why User Experience is Vital for the Success of Cloud Platforms

Next post

Starcounter's In-Memory Application Platform gets $1.8M Boost with New Funding