Open AntoineBachelet opened 2 years ago
@Leavingseason may have some ideas about this.
Any updates on this?
Description
I am actually using xDeepFM to find recommendation with implicit feedbacks and I did not find examples on how to find top-k recommendation with the model. I tried to use the function model.predict() with a file containing all the possible interactions between my users and items to find a score for each pair and sorting these scores to find top-k recommendation. This method gives me the same recommendation for every user so I would want to know if my method is wrong and what would you suggest to find top-k recommendation ?
Did you find a way to do top-k recommendation with it?
I worked on it during my internship, so I am not working on it anymore. But as far as I remember I used this technique (predict on every pair of user/item and sort to have top-k score) and acted on the different parameters of the model to have better results on my recommendations
Didnt you too get always the same recommendation for every user? (as you described in your post)
No, it seems that is was related with the parameter of the model trained (my model was underfitting) and the quality of the data I had (which was difficult to improve)
ok then i have to check my data. thanks for your help
Description
I am actually using xDeepFM to find recommendation with implicit feedbacks and I did not find examples on how to find top-k recommendation with the model. I tried to use the function model.predict() with a file containing all the possible interactions between my users and items to find a score for each pair and sorting these scores to find top-k recommendation. This method gives me the same recommendation for every user so I would want to know if my method is wrong and what would you suggest to find top-k recommendation ?