Universal Model for Paraphrasing

Using Transformation Based on a Defined Criteria

Abstract

Studies on paraphrasing are important in various research topics such as sentence generation, summarization, and question-answering. A universal model is described for paraphrasing that transforms according to defined criteria. We show that by using different criteria, we can construct different kinds of paraphrasing systems including one for compressing sentences, one for polishing the sentences up, one for transforming written language into spoken language, one for transforming English words into synonyms with the same meaing containing less “l” and “r” letters, and one for answering questions. Our model efficiently constructs systems and produces dynamic paraphrasing systems. It should prompt the creation of new paraphrasing systems in the feature.