Reviews: Learning Disentangled Representations for Recommendation

However, the whole framework makes sense to me, and the use of Gumbel-softmax trick and cosine similarity is also reasonable. MultDAE) in Figure 2, so that we can see the comparison. As learning such an item representation (distinguished by category, like clustering) is not hard. The micro disentanglement (Figure 3) is interesting, but the quantitative measurement is missing. Maybe the proposed macro-micro structure alleviates the data sparsity problem in some way?