Machine Learning Usecases for Pinterest.com & related Kosei Acquisition

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This article represents thoughts on recent acquisition of Kosei, a commerce recommendation system, by Pinterest.com. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos.

Following are the key points described later in this article:

  • How could Machine Learning help Pinterest fuel its overall growth?
  • How could Kosei help Pinterest.com?

 

How could Machine Learning help Pinterest fuel its overall growth?

Yet another acquisiton in the space of machine learning, Pinterest.com acquires Kosei to achieve some of the following objective:

  • Better ad targeting for greater mometization from ad clicks. This looks to be a case of identifying users clusters based on their browsing behavior and displaying appropriate ads to users belonging to these clusters. It could be solved with machine learning algorithms related with clustering. Additionally, one could come up with a classifier/learner which learns about clickability of ads from users clicks and in turn, may display more appropriate ads in future. It may also impact overall ads design.
  • Enhanced Pins recommendation on users’ home page: This would help brands reach to right set of people based on their browsing behavior in the past. Also, in general, users would be presented with pins that matches with their browsing behavior. As like above, this also look to be clustering problem where users with similar attributes are identified in different clusters and pins are appropriate targeted for these users cluster.
  • Product discovery & recommendations: Machine learning clustering algorithms could easily help recommend users to follow other users who post pins similar to their likings and, in turn, strengthen social networking aspect of the website.

 

How could Kosei help Pinterest.com?

Kosei reportedly have a very commerce recommendation system in place and it comes with a strong machine learning/data science team to Pinterest. It could help Pinterest in some of the follwing:

  • Strong team capable enough to create a machine learning system that could achieve some of the above-mentioned objectives
  • From product perspective, they could help design & develop following system:
    • Recommendation system for pins recommendation
    • Better Ad targeting system
    • Link building

 

Ajitesh Kumar

Ajitesh Kumar

Ajitesh has been recently working in the area of AI and machine learning. Currently, his research area includes Safe & Quality AI. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc.

He has also authored the book, Building Web Apps with Spring 5 and Angular.
Ajitesh Kumar

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