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We present a natural language system which summarizes a series of news articles on the same event. It uses summarization operators, identified through empirical analysis of a corpus of news summaries, to group empirical analysis of a corpus of news summaries, to group together templates from the output of the systems developed for ARPA's Message Understanding Conferences. Depending on the available resources(e.g. space), summaries of different length can be produced. Our research also provides a methodological frame work for future work on the summarization task and on the evaluation of new summarization systems.
McKeown et al. (Sun,) studied this question.