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Automatic Generation of Draft Summaries : Heuristics for Content Selection

We report on work aimed at providing discourse strategies for the automatic generation of draft scientific summaries. We have developed a discourse model based upon a theory of discourse structure and an analysis of data corresponding to available physics abstracts and naturally produced summaries written by domain-expert writers. In this paper, we present the results of our analyses and outline some derived heuristics for compression of discourse structures that convey a selected degree of detail. When applied to the data, the heuristics provided coherent and clear summaries, significantly shorter than the originals. These heuristics guide the process of compression in the automatic summary generator that is currently under development.