Simplicity is Better: Revisiting Single Kernel PPI Extraction

Abstract

It has been known that a combination of multiple kernels and addition of various resources are the best options for im-proving effectiveness of kernel-based PPI extraction methods. These supple-ments, however, involve extensive ker-nel adaptation and feature selection processes, which attenuate the original benefits of the kernel methods. This pa-per shows that we are able to achieve the best performance among the state-of-the-art methods by using only a sin-gle kernel, convolution parse tree kernel. In-depth analyses of the kernel reveal that the keys to the improvement are the tree pruning method and consideration of tree kernel decay factors. It is note-worthy that we obtained the perfor-mance without having to use any addi-tional features, kernels or corpora. 1