ROUGE Score

A ROUGE Score is a recall-oriented n-gram-based text similarity score produced by a ROUGE metric.

• Context:
  • It can typically quantify ROUGE Content Overlap between ROUGE system-generated summarys and ROUGE reference summarys.
  • It can typically represent ROUGE Recall Values indicating ROUGE reference coverage.
  • It can typically express ROUGE Precision Values measuring ROUGE system accuracy.
  • It can typically combine into ROUGE F-Scores through ROUGE harmonic mean computation.
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  • It can often correlate with ROUGE Human Judgments in ROUGE summarization evaluation.
  • It can often serve as ROUGE Benchmark Metrics in ROUGE NLP competitions.
  • It can often enable ROUGE System Comparisons through ROUGE standardized scoring.
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  • It can range from being a Low ROUGE Score to being a High ROUGE Score, depending on its ROUGE summary quality.
  • It can range from being a ROUGE Recall-Only Score to being a ROUGE F-Measure Score, depending on its ROUGE scoring mode.
  • It can range from being a ROUGE Single-Reference Score to being a ROUGE Multi-Reference Score, depending on its ROUGE reference configuration.
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  • It can be computed by ROUGE Scoring Algorithms using ROUGE matching rules.
  • It can be normalized through ROUGE Score Normalization for ROUGE cross-task comparison.
  • It can be aggregated via ROUGE Score Averaging across ROUGE document sets.
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• Example(s):
  • ROUGE-1 Scores, which measure ROUGE unigram overlap percentage.
  • ROUGE-2 Scores, which calculate ROUGE bigram matching rate.
  • ROUGE-N Scores, which compute ROUGE n-gram similarity value.
  • ROUGE-L Scores, which determine ROUGE LCS-based similarity.
  • ROUGE-W Scores, which provide ROUGE weighted LCS score.
  • ROUGE-S Scores, which generate ROUGE skip-bigram score.
  • ROUGE-SU Scores, which combine ROUGE skip-bigram and unigram score.
  • ...
• Counter-Example(s):
  • BLEU Score, which emphasizes precision-based MT evaluation rather than ROUGE recall-based summarization evaluation.
  • METEOR Score, which includes semantic similarity beyond ROUGE exact matching.
  • BERTScore, which uses neural embedding similarity instead of ROUGE n-gram overlap.
  • Human Evaluation Score, which reflects subjective quality assessment rather than ROUGE automatic scoring.
• See: Automatic Text Summarization, Evaluation Score, Recall Metric, Precision Metric, F-Measure, Text Similarity, NLG Evaluation.

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