An adaptation of a F-measure for automatic text summarization by extraction

In this paper, we propose to adapt the F-measure to evaluate an automatic summaries of texts; we the main key to our proposal is to prove that the automatic summary task can be modeled in supervised classification. First, we will start the research by to make a comparison between the automatic summary task and the supervised classification. After that, we are going to define how to draw a confusion matrix which classification evaluation base, and from it we calculate the F-Measure. In this vein, we must prove that the new measure is valid and trustworthy, And for this we will calculates the correlation with ROUGE Evaluation. Before ending we analyze and interpret the main results in order to answer the questions put forward in this research. At the end, we are going to conclude our study with a set of facts based on the collected data.