The traditional frequency based approach to creating multi-document extractive summary ranks sentences on scores computed by summing up TF*IDF weights of words contained in the sentences. In this approach, TF or term is calculated how frequently a (word) occurs input and way does not take into account semantic relations among terms. paper, we propose methods that exploits for improving sentence...

In this study, we introduce and evaluate a novel extractive text summarization methodology, “SummarEyes,” based on the visual interaction of user with text, using eye-tracking data, as opposed to traditional approaches analysis textual content only. We conducted large-scale study aiming collect data while reading be summarized. utilized various user’s implicit attention metrics generate eye-tra...