A Linear Kernel on Strongly Typed Terms

Support vector machines and other kernel methods have successfully been applied to various tasks in attribute-value learning. A kernel function is any function in input space that corresponds to an inner product in some feature space. In this discussion paper, we propose a kernel function on strongly typed first-order terms, and we show how this kernel corresponds to the linear inner product in a feature space containing a propositionalised description of the individuals.