Compared with CNN, it replaces the scalar-output feature detectors with vector-output capsules and has the ability to preserve additional information such as position and thickness.
formally, we apply a fusing convolution operation to the sentence embedding X with a kernel f a ∈ R d h ×K , and we get the aspect routing weight a i : where e a is the aspect embedding (or average embedding in the case of multi-word aspect), T a ∈ R 1×dw is a transfer matrix to map e a to a scalar value, and b a is bias.