A semantically enhanced approach to determine textual similarity

Eduardo Blanco, Dan Moldovan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper presents a novel approach to determine textual similarity. A layered methodology to transform text into logic forms is proposed, and semantic features are derived from a logic prover. Experimental results show that incorporating the semantic structure of sentences is beneficial. When training data is unavailable, scores obtained from the logic prover in an unsupervised manner outperform supervised methods.

Original languageEnglish (US)
Title of host publicationEMNLP 2013 - 2013 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages1235-1245
Number of pages11
ISBN (Electronic)9781937284978
StatePublished - 2013
Externally publishedYes
Event2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013 - Seattle, United States
Duration: Oct 18 2013Oct 21 2013

Publication series

NameEMNLP 2013 - 2013 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Conference

Conference2013 Conference on Empirical Methods in Natural Language Processing, EMNLP 2013
Country/TerritoryUnited States
CitySeattle
Period10/18/1310/21/13

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Information Systems
  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'A semantically enhanced approach to determine textual similarity'. Together they form a unique fingerprint.

Cite this