  There is evidence that address matching plays a crucial role in many areas
such as express delivery, online shopping and so on. Address has a hierarchical
structure, in contrast to unstructured texts, which can contribute valuable
information for address matching. Based on this idea, this paper proposes a
novel method to leverage the hierarchical information in deep learning method
that not only improves the ability of existing methods to handle irregular
address, but also can pay closer attention to the special part of address.
Experimental findings demonstrate that the proposed method improves the current
approach by 3.2% points.
