Hierarchical directed acyclic graph kernel

This paper devises a novel kernel function for natural language processing tasks. The new kernels, called Hierarchical Directed Acyclic Graph (HDAG) kernels, directly accept graphs whose nodes could contain graphs. HDAG data structures are needed to fully reflect the syntactic and semantic structures inherently possessed by natural language data. In this paper, we define the kernel function and describe how to achieve efficient calculation. Experimental results demonstrate that the proposed kernels are superior to other kernel functions, sequence kernels, dependency structure kernels, and bag-of-words kernels.