Extracting the Essence: Automatic Text Summarization

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Author(s): Fu Lee Wang (City University of Hong Kong, Hong Kong)and Christopher C. Yang (Drexel University, USA)
Copyright: 2009
Pages: 9
Source title: Handbook of Research on Digital Libraries: Design, Development, and Impact
Source Author(s)/Editor(s): Yin-Leng Theng (Nanyang Technological University, Singapore), Schubert Foo (Nanyang Technological University, Singapore), Dion Goh (Nanyang Technological University, Singapore)and Jin-Cheon Na (Nanyang Technological University, Singapore)
DOI: 10.4018/978-1-59904-879-6.ch011

Keywords: Digital Libraries / Information Science Reference / Library & Information Science / Library Science

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Abstract

As more information becomes available online, information-overloading results. This problem can be resolved through the application of automatic summarization. Traditional summarization models consider a document as a sequence of sentences. Actually, a large document has a well-defined hierarchical structure. Human abstractors use the hierarchical structure of the document to extract topic sentences. They start searching for topic sentences from the top level of the document structure downwards. Similarly, hierarchical summarization generates a summary for a document based on the hierarchical structure and salient features of the document. User evaluations that have been conducted indicate that hierarchical summarization outperforms traditional summarization.

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Extracting the Essence: Automatic Text Summarization

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