Reference-Based Accuracy Metric

A Reference-Based Accuracy Metric is an accuracy metric that is an automatic evaluation metric that can support reference-based evaluation tasks by comparing system outputs with gold-standard references.

• AKA: Supervised Accuracy Metric, Gold-Standard Metric, Reference-Dependent Metric, Comparison-Based Metric.
• Context:
  • It can typically align System Hypothesises with reference annotations.
  • It can typically measure Output Overlap between system predictions and gold-standard answers.
  • It can typically compute Precision Scores for accuracy assessment.
  • It can typically calculate Recall Scores for coverage evaluation.
  • It can typically generate F-Scores through harmonic mean calculation.
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  • It can often handle Multiple References for variation accommodation.
  • It can often weight Feature Types differently in scoring schemes.
  • It can often normalize Score Values by input length.
  • It can often provide Statistical Significance Tests for performance comparison.
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  • It can range from being a Strict Reference-Based Accuracy Metric to being a Flexible Reference-Based Accuracy Metric, depending on its matching tolerance.
  • It can range from being a Token-Level Reference-Based Accuracy Metric to being a Document-Level Reference-Based Accuracy Metric, depending on its evaluation granularity.
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  • It can integrate with Alignment Algorithm for correspondence extraction.
  • It can interface with Annotation Tool for reference processing.
  • It can connect to Evaluation Framework for systematic assessment.
  • It can synchronize with Benchmark Dataset for standardized testing.
  • It can communicate with Scoring Engine for performance calculation.
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• Example(s):
  • Natural Language Processing Reference-Based Accuracy Metrics, such as:
    • Machine Translation Reference-Based Accuracy Metrics like BLEU Score and METEOR Score.
    • Grammatical Error Correction Reference-Based Accuracy Metrics for error correction evaluation.
    • Text Summarization Reference-Based Accuracy Metrics like ROUGE Score.
  • Information Retrieval Reference-Based Accuracy Metrics, such as:
    • Precision-at-K Metric for ranked retrieval evaluation.
    • Mean Average Precision for retrieval system assessment.
    • Normalized Discounted Cumulative Gain for ranking quality measurement.
  • Classification Reference-Based Accuracy Metrics, such as:
    • Multi-Class Accuracy Metric for categorical prediction.
    • Binary Classification F1 Score for two-class problem.
    • Macro-Averaged F-Score for imbalanced dataset evaluation.
  • ...
• Counter-Example(s):
  • Reference-Free Quality Metric, which evaluates without gold-standard annotations.
  • Intrinsic Evaluation Metric, which measures internal propertys rather than output comparison.
  • User Satisfaction Metric, which captures subjective preference rather than objective accuracy.
• See: Accuracy Metric, Automatic Evaluation Metric, Gold Standard, F-Measure, Precision and Recall, Evaluation Framework, Performance Metric.

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