ParaEval: Using Paraphrases to Evaluate Summaries Automatically

نویسندگان

  • Liang Zhou
  • Chin-Yew Lin
  • Dragos Stefan Munteanu
  • Eduard H. Hovy
چکیده

ParaEval is an automated evaluation method for comparing reference and peer summaries. It facilitates a tieredcomparison strategy where recall-oriented global optimal and local greedy searches for paraphrase matching are enabled in the top tiers. We utilize a domainindependent paraphrase table extracted from a large bilingual parallel corpus using methods from Machine Translation (MT). We show that the quality of ParaEval’s evaluations, measured by correlating with human judgments, closely resembles that of ROUGE’s.

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تاریخ انتشار 2006