Evaluation of text summaries without human references based on the linear optimization of content metrics using a genetic algorithm

Highlights：

• The proposed evaluation provides a better correlation than state-of-the-art methods.

• 31 state-of-the-art metrics are combined to generate an optimized evaluation metric.

• The proposed evaluation method enables a balanced correlation improvement.

• The relevance of evaluation metrics presents a direct relation of individual correlation.

• State-of-the-art metrics with higher correlations improve the resultant final rank.