google-research / recsim

A Configurable Recommender Systems Simulation Platform
https://github.com/google-research/recsim
Apache License 2.0
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Problem of Large action spaces in interest evolution #23

Open riskr12 opened 2 years ago

riskr12 commented 2 years ago

I am trying to use RecSim(decompose_q with interest evolution) for training of recommendation. My action space( video ) is quite large and one-hot encoding will not work as we do in interest_evolution environment. Can you please suggest some other methodology by which we can simulate the environment.

cwhsu-google commented 2 years ago

Hi,

Sorry for the late reply. You probably need an embedding layer mapping from videos to action encoding and more thoughts on how we enumerate action/slate space efficiently. Thanks for using RecSim.

On Wed, Mar 9, 2022 at 3:28 AM riskr12 @.***> wrote:

I am trying to use RecSim(decompose_q with interest evolution) for training of recommendation. My action space( video ) is quite large and one-hot encoding will not work as we do in interest_evolution environment. Can you please suggest some other methodology by which we can simulate the environment.

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