Paper: Application-driven Statistical Paraphrase Generation

ACL ID P09-1094
Title Application-driven Statistical Paraphrase Generation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009

Paraphrase generation (PG) is important in plenty of NLP applications. However, the research of PG is far from enough. In this paper, we propose a novel method for statistical paraphrase generation (SPG), which can (1) achieve various applications based on a uniform statistical model, and (2) naturally combine multiple resources to enhance the PG performance. In our experiments, we use the proposed method to generate paraphrases for three differ- ent applications. The results show that the method can be easily transformed from one application to another and generate valuable and interesting paraphrases.