DLS$@$CU at SemEval-2016 Task 1: Supervised Models of Sentence Similarity

Md Arafat Sultan, Steven Bethard, Tamara Sumner
2016 Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)  
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.
doi:10.18653/v1/s16-1099 dblp:conf/semeval/SultanBS16 fatcat:sr4pqsv74bg37m3a6r5xarmvnq