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In this paper we describe our system (DTSim) submitted at SemEval-2016 Task 1: Semantic Textual Similarity (STS Core). We developed Support Vector Regression model with various features including the similarity scores calculated using alignment based methods and semantic composition based methods. The correlations between our system output and the human ratings were above 0.8 in three datasets.

DTSim at SemEval-2016 Task 1: Semantic Similarity Model Including Multi-Level Alignment and Vector-Based Compositional Semantics