Classification-based Contextual Preferences

Shachar Mirkin, Ido Dagan, Lili Kotlerman, Idan Szpektor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper addresses context matching in textual inference. We formulate the task under the Contextual Preferences framework which broadly captures contextual aspects of inference. We propose a generic classification-based scheme under this framework which coherently attends to context matching in inference and may be employed in any inference-based task. As a test bed for our scheme we use the Name-based Text Categorization (TC) task. We define an integration of Contextual Preferences into the TC setting and present a concrete self-supervised model which instantiates the generic scheme and is applied to address context matching in the TC task. Experiments on standard TC datasets show that our approach outperforms the state of the art in context modeling for Name-based TC.

Original languageEnglish
Title of host publicationTextInfer 2011 - Workshop on Textual Entailment at the Conference on Empirical Methods in Natural Language Processing, EMNLP 2011 - Proceedings
EditorsSebastian Pado, Stefan Thater
PublisherAssociation for Computational Linguistics (ACL)
Pages20-29
Number of pages10
ISBN (Electronic)1937284158, 9781937284152
StatePublished - 2011
Event2011 Workshop on Textual Entailment, TextInfer 2011 at the Conference on Empirical Methods in Natural Language Processing, EMNLP 2011 - Edinburgh, United Kingdom
Duration: 30 Jul 2011 → …

Publication series

NameTextInfer 2011 - Workshop on Textual Entailment at the Conference on Empirical Methods in Natural Language Processing, EMNLP 2011 - Proceedings

Conference

Conference2011 Workshop on Textual Entailment, TextInfer 2011 at the Conference on Empirical Methods in Natural Language Processing, EMNLP 2011
Country/TerritoryUnited Kingdom
CityEdinburgh
Period30/07/11 → …

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computational Theory and Mathematics
  • Information Systems

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