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Extracting the Essence: Automatic Text Summarization

Extracting the Essence: Automatic Text Summarization

Fu Lee Wang, Christopher C. Yang
Copyright: © 2009 |Pages: 9
ISBN13: 9781599048796|ISBN10: 1599048795|EISBN13: 9781599048802
DOI: 10.4018/978-1-59904-879-6.ch011
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MLA

Wang, Fu Lee, and Christopher C. Yang. "Extracting the Essence: Automatic Text Summarization." Handbook of Research on Digital Libraries: Design, Development, and Impact, edited by Yin-Leng Theng, et al., IGI Global, 2009, pp. 113-121. https://doi.org/10.4018/978-1-59904-879-6.ch011

APA

Wang, F. L. & Yang, C. C. (2009). Extracting the Essence: Automatic Text Summarization. In Y. Theng, S. Foo, D. Goh, & J. Na (Eds.), Handbook of Research on Digital Libraries: Design, Development, and Impact (pp. 113-121). IGI Global. https://doi.org/10.4018/978-1-59904-879-6.ch011

Chicago

Wang, Fu Lee, and Christopher C. Yang. "Extracting the Essence: Automatic Text Summarization." In Handbook of Research on Digital Libraries: Design, Development, and Impact, edited by Yin-Leng Theng, et al., 113-121. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-59904-879-6.ch011

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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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