AMR到文本生成作为一个旅行推销员问题
AMR-to-text generation as a Traveling Salesman Problem
摘要：
AMR到文本生成的任务是为给定的AMR图生成维持语义含义的语法文本。首先将AMR图分割成较小的片段，然后为每个片段生成翻译，最后通过解决非对称广义旅行商问题（AGTSP）来决定顺序。训练最大熵分类器来估计旅行成本，并使用TSP求解器来找到最优解。最终模型在SemEval-2016 Task 8数据集上报告的BLEU得分为22.44。
英文摘要：
The task of AMR-to-text generation is to generate grammatical text that sustains the semantic meaning for a given AMR graph. We at- tack the task by first partitioning the AMR graph into smaller fragments, and then generating the translation for each fragment, before finally deciding the order by solving an asymmetric generalized traveling salesman problem (AGTSP). A Maximum Entropy classifier is trained to estimate the traveling costs, and a TSP solver is used to find the optimized solution. The final model reports a BLEU score of 22.44 on the SemEval-2016 Task8 dataset.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
