a hybrid statistical/linguistic model for generating news story gists
In this paper, we describe a News Story Gisting system that generates a 10-word short summary of a news story. This system uses a machine learning technique to combine linguistic, statistical and positional information in order to generate an appropriate summary. We also present the results of an automatic evaluation of this system with respect to the performance of other baseline summarisers using the new ROUGE evaluation metric.
news story gisting machine learning summarisation lexical cohesion