In this paper, we propose a novel class of graphs, the tripartite directed acyclic graphs (tDAGs), to model first-order rule feature spaces for sentence pair classification. We introduce a novel algorithm for computing the similarity in first-order rewrite rule feature spaces. Our algorithm is extremely efficient and, as it computes the similarity of instances that can be represented in explicit feature spaces, it is a valid kernel function.
Zanzotto, F.m., Dell'Arciprete, L. (2009). Efficient kernels for sentence pair classification. In Proceedings of the 2009 Conference on Empirical Methods on Natural Language Processing (EMNLP) - http://www.scimagojr.com/journalsearch.php?q=19900195077&tip=sid&clean=0 - (GGS Conference Ranking 1 A+) (pp.91-100). Stroudsburg : Association for Computational Linguistics (ACL).
Efficient kernels for sentence pair classification
ZANZOTTO, FABIO MASSIMO;
2009-01-01
Abstract
In this paper, we propose a novel class of graphs, the tripartite directed acyclic graphs (tDAGs), to model first-order rule feature spaces for sentence pair classification. We introduce a novel algorithm for computing the similarity in first-order rewrite rule feature spaces. Our algorithm is extremely efficient and, as it computes the similarity of instances that can be represented in explicit feature spaces, it is a valid kernel function.| File | Dimensione | Formato | |
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