@inproceedings{Pahikkala:EtAl:06,
title = {Graph Kernels versus Graph Representations: A Case Study in Parse Ranking},
author = {Tapio Pahikkala and Evgeni Tsivtsivadze and Jorma Boberg and Tapio Salakoski},
booktitle = {ECML/PKDD Workshop on Mining and Learning with Graphs},
url = {http://www.inf.uni-konstanz.de/mlg2006/19.pdf},
year = {2006},
abstract = {Recently, several kernel functions designed for a data that consists of graphs have been presented. In this paper, we concentrate on designing graph representations and adapting the kernels for these graphs. In particular, we propose graph representations for dependency parses and analyse the applicability of several variations of the graph kernels for the problem of parse ranking in the domain of biomedical texts. The parses used in the study are generated with the link grammar (LG) parser from annotated sentences of BioInfer corpus. The results indicate that designing the graph representation is as important as designing the kernel function that is used as the similarity measure of the graphs.},
keywords = {2006 graphs kernels structure workshop }
}
::