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Re: How to build a recommender system?
Date: April 24, 2019 12:06PM
There are many types of recommendations that you may want to make. The type that is most obviously applicable to SPMF is called item to item recommendations. You can think of this like cross-sell. If you land on a page for product A recommendation might be for items that sell well with product A. This is what is described in the association rules section of SPMF.
Otherwise, to my knowledge, most companies do not use data mining. Modern techniques are often built using neural networks. If you would like to see some basic recommender system implementations, I recommend reading through the Lightfm and Spotlight implementations in python (linked below). Lightfm uses matrix decomposition to find similar items and users, while spotlight (same author) uses deep neural networks to identify common purchasing sequences. A good basic article on building one of these systems from scratch is the deep beers medium article: