In order to fuse word-level and sentence-level information from different semantic spaces, the authors propose a hybrid optimization framework to optimize word-level information while simultaneously incorporate sentence-level information as constraints. The optimization is conducted by iterative unit substitutions. The performance on DUC benchmark datasets demonstrates the effectiveness of proposed framework in terms of ROUGE evaluation.
