If the output (classification) score belongs to the positive class, i S will be selected as part of the summary; otherwise, it will be excluded (Kupiec et al., 1999).
the problem can be formulated as follows: Construct a sentence ranking model that assigns a classification score (or a posterior probability) of being in the summary class to each sentence of a spoken document to be summarized; important sentences are subsequently ranked and selected according to these scores.