A Robust Practical Text Summarization

Tomek Strzalkowski; Wang, Jin; Wise, Bowden

We present an automated method of generating human-readable summaries from text documents such as news, technical reports, government documents, and even court records. Our approach exploits an empirical observation that much of the written text display certain regularities of organization and style, which we call the Discourse Macro Structure (DMS). A summary is therefore created to reflect the components of a given DMS. In order to produce a coherent and readable summary we select continuous, well-formed passages from the source document and assemble them into a mini-document within a DMS template. In this paper we describe the SummarizerTool, a Java-implemented prototype, and its applications in various document processing tasks.

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