Fast and effective kernels for relational learning from texts

Alessandro Moschitti, Fabio Massimo Zanzotto
2007 Proceedings of the 24th international conference on Machine learning - ICML '07  
In this paper, we define a family of syntactic kernels for automatic relational learning from pairs of natural language sentences. We provide an efficient computation of such models by optimizing the dynamic programming algorithm of the kernel evaluation. Experiments with Support Vector Machines and the above kernels show the effectiveness and efficiency of our approach on two very important natural language tasks, Textual Entailment Recognition and Question Answering.
doi:10.1145/1273496.1273578 dblp:conf/icml/MoschittiZ07 fatcat:2hiqwcsefjfilopzzidcxrx6h4