18:00 - 18:30 : Gathering
18:30 - 20:00 : Interaction Based Feature Extraction: How to Convert Your Users’ Activity into Valuable Features.
Today almost every website and app collect data about the interactions (clicks, likes, views...)
between users and items. The most common use case for these sparse “user-item” matrices is to
train and improve different recommendation systems.
In my presentation I will introduce how we can use exactly the same matrices together with
additional datasets to generate valuable features that can be used to train different regression and
I will start with describing how it was implemented at SimilarWeb, in order to accurately estimate
different website metrics like demographics (age and gender) and category and continue with
explaining how we can expand the algorithm to solve similar problems in different domains.
Shlomi Babluki (https://il.linkedin.com/in/shlomi-babluki-1a29289
) , Data Analysis Team Leader, SimilarWeb.
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