A weighted polynomial information gain kernel for resolving prepositional phrase attachment ambiguities with support vector machines
Bram Vanschoenwinkel, Bernard Manderick · 2003
We introduce a new kernel for Support Vector Machine learning in a natural language setting. As a case study to incorporate domain knowledge into a kernel, we consider the problem of resolving Prepositional Phrase attachment ambiguities. The new kernel is derived from a distance function that proved to be succesful in memory-based learning. We start with the