Paper: Efficient kernels for sentence pair classification

ACL ID D09-1010
Title Efficient kernels for sentence pair classification
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors

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 classifi- cation. 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 rep- resented in explicit feature spaces, it is a valid kernel function.