A logic prover approach to predicting textual similarity

Eduardo Blanco, Dan Moldovan

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

4 Scopus citations

Abstract

This paper presents a logic prover approach to predicting textual similarity. Sentences are represented using three logic forms capturing different levels of knowledge, from only content words to semantic representations extracted with an existing semantic parser. A logic prover is used to find proofs and derive semantic features that are combined in a machine learning framework. Experimental results show that incorporating the semantic structure of sentences yields better results than simpler pairwise word similarity measures.

Original languageEnglish (US)
Title of host publicationFLAIRS 2013 - Proceedings of the 26th International Florida Artificial Intelligence Research Society Conference
Pages255-258
Number of pages4
StatePublished - 2013
Externally publishedYes
Event26th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2013 - St. Pete Beach, FL, United States
Duration: May 22 2013May 24 2013

Publication series

NameFLAIRS 2013 - Proceedings of the 26th International Florida Artificial Intelligence Research Society Conference

Other

Other26th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2013
Country/TerritoryUnited States
CitySt. Pete Beach, FL
Period5/22/135/24/13

ASJC Scopus subject areas

  • Artificial Intelligence

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