This paper presents our submissions for semantic textual similarity task in SemEval 2016. Based on several traditional features (i.e., string-based, corpus-based, machine translation similarity and alignment metrics), we leverage word embedding from macro (i.e., first get representation of sentence, then measure the similarity of sentence pair) and micro views (i.e., measure the similarity of w...
