Older versions of the ROUGEeval summarization evaluation system were easier to fool

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摘要

We show some limitations of the ROUGE evaluation method for automatic summarization. We present a method for automatic summarization based on a Markov model of the source text. By a simple greedy word selection strategy, summaries with high ROUGE-scores are generated. These summaries would however not be considered good by human readers. The method can be adapted to trick different settings of the ROUGEeval package.

论文关键词：Automatic summarization,Automatic evaluation,Markov models

论文评审过程：Received 11 July 2006, Revised 3 January 2007, Accepted 8 January 2007, Available online 2 March 2007.

论文官网地址：https://doi.org/10.1016/j.ipm.2007.01.014