Comments (3)
AkihikoWatanabe
commented on June 12, 2024
重要論文
ユーザのアイテムに対するExplicit/Implicit Ratingを利用したlearning2rank。
AUCを最適化するようなイメージ。
負例はNegative Sampling。
計算量が軽く、拡張がしやすい。
Implicitデータを使ったTop-N Recsysを構築する際には検討しても良い。
また、MFのみならず、Item-Based KNNに活用することなども可能。
http://tech.vasily.jp/entry/2016/07/01/134825
from paper_notes.
AkihikoWatanabe
commented on June 12, 2024
参考: https://techblog.zozo.com/entry/2016/07/01/134825
from paper_notes.
AkihikoWatanabe
commented on June 12, 2024
pytorchでのBPR実装: https://github.com/guoyang9/BPR-pytorch
from paper_notes.
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