DLS$@$CU: Sentence Similarity from Word Alignment

Abstract

We present an algorithm for computing the semantic similarity between two sentences. It adopts the hypothesis that semantic similarity is a monotonically increasing function of the degree to which (1) the two sentences contain similar semantic units, and (2) such units occur in similar semantic contexts. With a simplistic operationalization of the notion of semantic units with individual words, we experimentally show that this hypothesis can lead to state-of-the-art results for sentencelevel semantic similarity. At the SemEval 2014 STS task (task 10), our system demonstrated the best performance (measured by correlation with human annotations) among 38 system runs.

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Cite this paper

@inproceedings{Sultan2014DLSCUSS, title={DLS\$@\$CU: Sentence Similarity from Word Alignment}, author={Md. Arafat Sultan and Steven Bethard and Tamara Sumner}, booktitle={SemEval@COLING}, year={2014} }