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Sentence Compression via DC Programming Approach

  • Yi-Shuai NiuEmail author
  • Xi-Wei Hu
  • Yu You
  • Faouzi Mohamed Benammour
  • Hu Zhang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 991)

Abstract

Sentence compression is an important problem in natural language processing. In this paper, we firstly establish a new sentence compression model based on the probability model and the parse tree model. Our sentence compression model is equivalent to an integer linear program (ILP) which can both guarantee the syntax correctness of the compression and save the main meaning. We propose using a DC (Difference of convex) programming approach (DCA) for finding local optimal solution of our model. Combing DCA with a parallel-branch-and-bound framework, we can find global optimal solution. Numerical results demonstrate the good quality of our sentence compression model and the excellent performance of our proposed solution algorithm.

Keywords

Sentence compression Probability model Parse Tree Model DCA Parallel-branch-and-bound 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of Mathematical SciencesShanghai Jiao Tong UniversityShanghaiChina
  2. 2.SJTU-Paristech Elite Institute of TechnologyShanghai Jiao Tong UniversityShanghaiChina

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