DLS@CU at SemEval-2016 task 1: Supervised models of sentence similarity

Md Arafat Sultan, Steven Bethard, Tamara Sumner

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

2 Scopus citations

Abstract

We describe a set of systems submitted to the SemEval-2016 English Semantic Textual Similarity (STS) task. Given two English sentences, the task is to compute the degree of their semantic similarity. Each of our systems uses the SemEval 2012-2015 STS datasets to train a ridge regression model that combines different measures of similarity. Our best system demonstrates 73.6% correlation with average human annotations across five test sets.

Original languageEnglish (US)
Title of host publicationSemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages650-655
Number of pages6
ISBN (Electronic)9781941643952
DOIs
StatePublished - 2016
Externally publishedYes
Event10th International Workshop on Semantic Evaluation, SemEval 2016 - San Diego, United States
Duration: Jun 16 2016Jun 17 2016

Publication series

NameSemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings

Conference

Conference10th International Workshop on Semantic Evaluation, SemEval 2016
Country/TerritoryUnited States
CitySan Diego
Period6/16/166/17/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Computer Science Applications

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