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Recommendation Algorithm大规模推荐算法库,包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESMM、MAML、xDeepFM、DeepFEFM、NFM、AFM、RALM、DMR、GateNet、NAML、DIFM、Deep Crossing、PNN、BST、AutoInt、FGCNN、FLEN、Fibinet、ListWise、DeepRec、ENSFM,TiSAS,AutoFIS等,包含经典推荐系统数据集criteo 、movielens等

  • Updated Apr 27, 2022
  • Python
R7788380
R7788380 commented Nov 24, 2020

作者您好,關於 AttRec 這份模型我有些疑問,就是在預測時會使用到 Next positive item 的 embedding,照理來說預測時是不能夠把真正的 Next positive item 輸入給模型,這樣等於是把正確答案丟給模型,請問真正在預測時,要如何得到 pos_scoresneg_scores 呢 ?

以下是程式碼中使用到 pos_embed 時,會讓我產生的疑問:

 # combine
 pos_scores = self.w * tf.reduce_sum(tf.multiply(short_interest, pos_embed), axis=-1, keepdims=True) \+ 
                        (1 - self.w) * tf.reduce_sum(pos_long_intere
good first issue

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