Furthermore, the summary should be non-redundant (i.e., high entropy).
these two requirements are unified by the Kullback MDI principle: the least biased summary S * that best approximates the distribution P D K is the solution of: we note θ I as the quantity that scores summaries: Interpretation of P D K : P D K can be viewed as an importance-encoding distribution because it encodes the relative importance of semantic units and gives an overall target for the summary.