Paper: UoW: Multi-task Learning Gaussian Process for Semantic Textual Similarity

ACL ID S14-2138
Title UoW: Multi-task Learning Gaussian Process for Semantic Textual Similarity
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

We report results obtained by the UoW method in SemEval-2014?s Task 10 ? Mul- tilingual Semantic Textual Similarity. We propose to model Semantic Textual Simi- larity in the context of Multi-task Learning in order to deal with inherent challenges of the task such as unbalanced performance across domains and the lack of training data for some domains (i.e. unknown domains). We show that the Multi-task Learning approach outperforms previous work on the 2012 dataset, achieves a ro- bust performance on the 2013 dataset and competitive results on the 2014 dataset. We highlight the importance of the chal- lenge of unknown domains, as it affects overall performance substantially.