Ultra-summarization (poster abstract)

Using current extractive summarization techniques, it is impossible to produce a coherent document summary shorter than a single sentence, or to produce a summary that conforms to particular stylistic constraints. Ideally, one would prefer to understand the document, and to generate an appropriate summary directly from the results of that understanding. Absent a comprehensive natural language understanding system, an approximation must be used. This paper presents an alternative statistical model of a summarization process, which jointly applies statistical models of the term selection and term ordering process to produce brief coherent summaries in a style learned from a training corpus.