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About hit radio@50 in the evaluation of AttRec #31
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Usually, we only consider recommending those items that the user has never seen. If an item is liked by the user, we don't want to repeatedly recommend it to him. |
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hi,
In the evaluation process of AttRec, when calculating the recommendation item rank of each user, why use the negative items instead of all items?
this code in: DeepRec/utils/evaluation/SeqRecMetrics.py--->def evaluate1(self)
In my understanding, It should be to calculate the score of each user and all items, then rank them, and finally take the top 50 to calculate HT@50.
Calculate it the way the code says, it does not have any positive items in the prediction process.
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