We describe the system we developed to participate in SemEval 2015 Task 1, Paraphrase and Semantic Similarity in Twitter. We create similarity vectors from two-skip trigrams of preprocessed tweets and measure their semantic similarity using our UMBC-STS system. We submit two runs. The best result is ranked eleventh out of eighteen teams with F1 score of 0.599.
['Taneeya Satyapanich', 'Hang Gao', 'Tim Finin']
Ebiquity: Paraphrase and Semantic Similarity in Twitter using Skipgrams