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

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