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Let's say I am building a recommender system where items change through time. We suppose that each transaction is composed of :

  • an item $i$ in list of items $(i_1, i_2, i_3, .., i_m)$.
  • a user $u$ in list of users $(u_1, u_2, u_3, ..., u_n)$.
  • a date $t$ in list of dates $(t_1, t_2, ... t_k)$.

We suppose that items have underlying features that change over time.For example, If we consider retail products, underlying features could be :

  • The discount level that is applied on the item when the customer has purchased the transaction (5%, 10%, 20%, 30%, ...).

An other example, if we consider financial stocks, underlying features that change over time could be :

  • The stock situation at time of the transaction (underpriced or overpriced).
  • The stock's central bank politics at time of the transaction (low interest rates, medium interest rates, high interest rates).

We suppose that these underlying features have a strong impact on users. It completly drives their decisions to buy or not an object. If we consider two items $i_1$ and $i_2$, at time $t_1$, a given user $u_1$ could prefer $i_1$ over $i_2$ because $i_1$'s underlying features are more interesting than $i_2$'s. If we consider a different time, maybe $u_1$ could be more interested in $i_2$ than $i_1$.

My question is : how to take into account underlying features that change over time in recommender systems such as user-user collaborative filtering, SVD, ALS... ?.

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In the case of collaborative filtering where everything is done based on a rating matrix, then a change in the product's features should first be reflected into the new ratings of your users and therefore to the final recommendation.

This is done in the same way a user changes its preferences in time. usually two approaches are followed, creating time aware models (timeSVD++) where the rating drifts is modeled in time or through a time decaying function on the ratings. A good resource on the first opnes can be found here

If you are using a classification approach i.e if a user will use a product, then this should not be an issue.

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