Abstract
This paper describes SVCSTS, a system that was submitted in SemEval-2015 Task 2: Semantic Textual Similarity(STS)(Agirre et al., 2015). The task has 3 subtasks viz., English STS, Spanish STS and Interpretable STS. SVCSTS uses Monolingual word aligner (Sultan et al., May 2014), supervised machine learning, Google and Bing translator API's. Various runs of the system outperformed all other participating systems in Interpretable STS for non-chunked sentence input.
Cite
CITATION STYLE
Karumuri, S., Vuggumudi, V. K. R., & Chitirala, S. C. R. (2015). UMDuluth-BlueTeam: SVCSTS - A Multilingual and Chunk Level Semantic Similarity System. In SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings (pp. 107–110). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s15-2019
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