Saarland: Vector-based models of semantic textual similarity.

This paper describes our system for the Semeval 2012 Sentence Textual Similarity task. The system is based on a combination of few simple vector space-based methods for word meaning similarity. Evaluation results show that a simple combination of these unsupervised data-driven methods can be quite successful. The simple vector space components achieve high performance on short sentences; on longer, more complex sentences, they are outperformed by a surprisingly competitive word overlap baseline, but they still bring improvements over this baseline when incorporated into a mixture model.