Publishing Partner: Cambridge University Press CUP Extra Publisher Login
amazon logo
More Info


New from Oxford University Press!

ad

Style, Mediation, and Change

Edited by Janus Mortensen, Nikolas Coupland, and Jacob Thogersen

Style, Mediation, and Change "Offers a coherent view of style as a unifying concept for the sociolinguistics of talking media."


New from Cambridge University Press!

ad

Intonation and Prosodic Structure

By Caroline Féry

Intonation and Prosodic Structure "provides a state-of-the-art survey of intonation and prosodic structure."


Academic Paper


Title: A machine learning approach to textual entailment recognition
Author: Fabio Massimo Zanzotto
Institution: Università degli Studi di Roma - La Sapienza
Author: Marco Pennacchiotti
Institution: Yahoo! Research
Author: Alessandro Moschitti
Institution: Università degli Studi di Trento
Linguistic Field: Computational Linguistics; Pragmatics; Semantics; Syntax
Abstract: Designing models for learning textual entailment recognizers from annotated examples is not an easy task, as it requires modeling the semantic relations and interactions involved between two pairs of text fragments. In this paper, we approach the problem by first introducing the class of pair feature spaces, which allow supervised machine learning algorithms to derive first-order rewrite rules from annotated examples. In particular, we propose syntactic and shallow semantic feature spaces, and compare them to standard ones. Extensive experiments demonstrate that our proposed spaces learn first-order derivations, while standard ones are not expressive enough to do so.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 15, Issue 4.

Return to TOC.

Add a new paper
Return to Academic Papers main page
Return to Directory of Linguists main page