Fast and effective kernels for relational learning from texts

  • Authors:
  • Alessandro Moschitti;Fabio Massimo Zanzotto

  • Affiliations:
  • University of Trento, Povo di Trento, Italy;University of Rome "Tor Vergata", Rome, Italy

  • Venue:
  • Proceedings of the 24th international conference on Machine learning
  • Year:
  • 2007

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Abstract

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.