A Weighted Polynomial Information Gain Kernel for Resolving Prepositional Phrase Attachment Ambiguities with Support Vector Machines (2003)
| Venue: | IN THE PROCEEDINGS OF THE EIGHTEENTH INTERNATIONAL JOINT CONFERENCES ON ARTIFICIAL INTELLIGENCE (IJCAI-03 |
| Citations: | 8 - 4 self |
BibTeX
@INPROCEEDINGS{Vanschoenwinkel03aweighted,
author = {Bram Vanschoenwinkel and Bernard Manderick},
title = {A Weighted Polynomial Information Gain Kernel for Resolving Prepositional Phrase Attachment Ambiguities with Support Vector Machines},
booktitle = {IN THE PROCEEDINGS OF THE EIGHTEENTH INTERNATIONAL JOINT CONFERENCES ON ARTIFICIAL INTELLIGENCE (IJCAI-03},
year = {2003},
pages = {133--138},
publisher = {}
}
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Abstract
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
