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ROUGE-SS: A New ROUGE Variant for Evaluation of Text Summarization
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Evaluation is the systematic collection and analysis of data to make
judgments about a software system’s value, worth or quality. The
authenticity or accuracy of any software system is based on evaluation
techniques. If the evaluation technique covers more features for
evaluating a software system, then it will be beneficial for determining
the proposed system’s accuracy, validity, and reliability. The ROUGE
score metrics and their variants are utilized for evaluating text
summarization models. While ROUGE metrics are suitable for extractive
approaches, they are inadequate for abstractive approaches as it rely on
exact word matching. Therefore, we have proposed a new variant of the
ROUGE metric called ROUGE-SS, which also considers word’s synonyms in
addition to exact matches. Our experiments have shown that ROUGE-SS is
more effective than other variants of ROUGE scores. The f1-score of
proposed ROUGE-SS metric is increase by an average of 8.8%.
Title: ROUGE-SS: A New ROUGE Variant for Evaluation of Text Summarization
Description:
Evaluation is the systematic collection and analysis of data to make
judgments about a software system’s value, worth or quality.
The
authenticity or accuracy of any software system is based on evaluation
techniques.
If the evaluation technique covers more features for
evaluating a software system, then it will be beneficial for determining
the proposed system’s accuracy, validity, and reliability.
The ROUGE
score metrics and their variants are utilized for evaluating text
summarization models.
While ROUGE metrics are suitable for extractive
approaches, they are inadequate for abstractive approaches as it rely on
exact word matching.
Therefore, we have proposed a new variant of the
ROUGE metric called ROUGE-SS, which also considers word’s synonyms in
addition to exact matches.
Our experiments have shown that ROUGE-SS is
more effective than other variants of ROUGE scores.
The f1-score of
proposed ROUGE-SS metric is increase by an average of 8.
8%.
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