A New Metric of Validation for Automatic Text Summarization by Extraction

In this article, the author proposes a new metric of evaluation for automatic summaries of texts. In this case, the adaptation of the F-measure that generates a hybrid method of evaluating an automatic summary at the same time as both extrinsic and intrinsic. The article starts by studying the feasibility of adaptation of the F-measure for the evaluation of automatic summarization. After that, the author defines how to calculate the F-measure for a candidate summary. Text is presented with a term vector which can be either a word or a phrase, with a binary-weighted or occurrence. Finally, to determine to the exactitude of evaluation of the F-measure for automatic summarization by extraction calculates correlation with the ROUGE Evaluation.