Efficient kernels for sentence pair classification

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.

• Type: Journal
• Year: 2009
• Where: EMNLP
• Authors: Fabio Massimo Zanzotto, Lorenzo Dell'Arciprete
• Keywords: EMNLP 2009, Explicit Feature Spaces, Natural Language Processing, Sentence Pair Classification, Valid Kernel Function