HHU at SemEval-2016 Task 1: Multiple Approaches to Measuring Semantic Textual Similarity
Matthias Liebeck, Philipp Pollack, Pashutan Modaresi, Stefan Conrad · 2016
This paper describes our participation in the SemEval-2016 Task 1: Semantic Textual Similarity (STS).We developed three methods for the English subtask (STS Core).The first method is unsupervised and uses WordNet and word2vec to measure a token-based overlap.In our second approach, we train a neural network on two features.The third method uses word2vec and LDA with regression splines.