Automatic summarising: The state of the art

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This paper reviews research on automatic summarising in the last decade. This work has grown, stimulated by technology and by evaluation programmes. The paper uses several frameworks to organise the review, for summarising itself, for the factors affecting summarising, for systems, and for evaluation.The review examines the evaluation strategies applied to summarising, the issues they raise, and the major programmes. It considers the input, purpose and output factors investigated in recent summarising research, and discusses the classes of strategy, extractive and non-extractive, that have been explored, illustrating the range of systems built.The conclusions drawn are that automatic summarisation has made valuable progress, with useful applications, better evaluation, and more task understanding. But summarising systems are still poorly motivated in relation to the factors affecting them, and evaluation needs taking much further to engage with the purposes summaries are intended to serve and the contexts in which they are used.

论文关键词:Summarization,Evaluation,Sentence extraction,Abstraction natural language processing

论文评审过程:Received 22 February 2007, Revised 5 March 2007, Accepted 13 March 2007, Available online 1 June 2007.

论文官网地址:https://doi.org/10.1016/j.ipm.2007.03.009