Leveraging Multiple MT Engines for Paraphrase Generation
This paper proposes a method that leverages multiple machine translation (MT) engines for paraphrase generation (PG). The method includes two stages. Firstly, we use a multi-pivot approach to acquire a set of candidate paraphrases for a source sentence S. Then, we employ two kinds of techniques, namely the selection-based technique and the decoding-based technique, to produce a best paraphrase T for S using the candidates acquired in the first stage. Experimental results show that: (1) The multi-pivot approach is effective for obtaining plenty of valuable candidate paraphrases. (2) Both the selectionbased and decoding-based techniques can make good use of the candidates and produce high-quality paraphrases. Moreover, these two techniques are complementary. (3) The proposed method outperforms a state-of-the-art paraphrase generation approach.
Shiqi Zhao Haifeng Wang Xiang Lan Ting Liu
Baidu Inc.HIT Center for Information Retrieval, Harbin Institute of Technology Baidu Inc. HIT Center for Information Retrieval, Harbin Institute of Technology
国际会议
The 23rd International Conference on Computational Linguistics(第23届国际计算语言学大会)
北京
英文
1326-1334
2010-08-01（万方平台首次上网日期，不代表论文的发表时间）