In this article, I wanted to share about a trend that’s occurred over the past few years of using the word2vec model on not just natural language tasks, but on recommender systems as well.

In part 1 of this tutorial, I described the most basic form of a product quantizer. In this post, I’ll be explaining the IndexIVFPQ index from the FAISS library, which uses a product quantizer as well as a couple additional techniques introduced in their 2011 paper.

This post was written in my role as a researcher at Nearist, and will soon be on the Nearist website as well.

I recently created a project on GitHub called wiki-sim-search where I used gensim to perform concept searches on English Wikipedia.