Abstract
We use referential translation machines (RTMs) for predicting the semantic similarity of text in both STS Core and Cross-lingual STS. RTMs pioneer a language independent approach to all similarity tasks and remove the need to access any task or domain specific information or resource. RTMs become 14th out of 26 submissions in Cross-lingual STS. We also present rankings of various prediction tasks using the performance of RTM in terms of MRAER, a normalized relative absolute error metric.
Cite
CITATION STYLE
Biçici, E. (2016). RTM at SemEval-2016 task 1: Predicting semantic similarity with referential translation machines and related statistics. In SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings (pp. 758–764). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s16-1117
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