Here, we embed each user u and each product p as continuous and realvalued vectors u ∈ R du and p ∈ R dp , where d u and d p are the dimensions of user embeddings and product embeddings respectively.
the attention weight α i j for each hidden state can be defined as: where e is a score function which scores the importance of words for composing sentence representation.