Augmentable Paraphrase Extraction Framework

Paraphrase extraction relying on a single factor such as distribution similarity or translation similarity might lead to the loss of some linguistic properties. In this paper, we propose a paraphrase extraction framework, which accommodates various linguistically motivated factors to optimize the quality of paraphrase extraction. The major contributions of this study lie in the augmentable paraphrasing framework and the three kinds of factors conducive to both semantic and syntactic correctness. A manual evaluation showed that our model achieves more successful results than the state-of-the-art methods.