tensorflow / tensorflow/recommenders
Including Implicit negative feedback
@maciejkula is already working on this.
Since Apr 27, 2021.
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Description
Hi,
Thanks for this great library!
This is a general question for some guidance or literature on the topic of implicit negative feedback.
The dataset I have relates to audio tracks. There can be various signals of implicit interest but the simplest and strongest is how much they listened to the track. Multiple times indicates strong preference whilst skipping is a pretty clear signal of dislike.
It would seem reasonable to assume that including this behaviour would improve the recommendations, but I can't seem to work out how to include it in a retrieval type model.
I've attempted including these in a multi-task learner, where the sample weight in the retrieval model is set low for these dislike examples, however it results some oscillations in the training loss, and ultimately worse recall from the retrieval model.
Are there any examples or ideas on how to do this?
Thanks in advanced!
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