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Research Papers

Multidocument Summarization of Engineering Papers Based on Macro- and Microstructure

[+] Author and Article Information
Jiaming Zhan, Han Tong Loh

Mechanical Engineering, National University of Singapore, Singapore 117576mpeliuy@nus.edu.sg

Ying Liu1

Mechanical Engineering, National University of Singapore, Singapore 117576mpeliuy@nus.edu.sg

See http://berouge.com/default.aspx.

1

Corresponding author.

J. Comput. Inf. Sci. Eng 11(1), 011008 (Mar 31, 2011) (12 pages) doi:10.1115/1.3563048 History: Received June 05, 2010; Revised January 12, 2011; Published March 31, 2011; Online March 31, 2011

This paper focuses on automatic summarization of multiple engineering papers. A summarization approach based on documents’ macro- and microstructure has been proposed. The macrostructure consists of a list of ranked topics from engineering papers. Topics are discovered by extracting and grouping frequently appearing word sequences into equivalence classes. Hence, the macrostructure symbolically presents the topical links in different papers. Meanwhile, the microstructure is defined as the rhetorical structure within a single paper. The identification of microstructure is approached as a classification problem. Each sentence in a paper is automatically labeled with one of the predefined rhetorical categories. Unlike existing summarization methods that first separate documents into nonoverlapping clusters and then summarize each cluster individually, our approach aims to summarize multiple documents according to the characteristics suggested at macro- and microstructure levels. The experimental study showed that our proposed approach outperformed peer systems in terms of recall-oriented understudy for gisting evaluation scores and readers’ responsiveness. In an independent manual categorization task using the summaries generated by our approach and peer systems, we also performed better in terms of precision and recall.

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References

Figures

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Figure 1

Literature review from Ref. 59. The topical sentence in each paragraph is highlighted.

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Figure 2

Discourse structures of three manual summaries (50 words) for a cohesive document set. These three summaries share the same meaning in their topical sentences: Hurricane Andrew was the costliest natural disaster in the United States up to that time, followed by sentences elaborating this topic. The structures in these three summaries are largely consistent, although the elaboration sentences in different summaries emphasize different aspects of the disaster and are presented in different orders.

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Figure 3

Discourse structures of three manual summaries (50 words) for document Set d11

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Figure 4

Discourse structures of three manual summaries (200 words) for document Set d11. These summaries all include the three major topics in the document set: (1) Some general facts regarding tornadoes, e.g., season, location, etc. (2) Fujita Scale measures for tornadoes proposed by Professor Tetsuya Theodore Fujita. (3) Mention of defining safety plans before tornadoes strike, and the meaning of “tornado watch” and warning.

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Figure 5

Flowchart of multipaper summarization based on macro- and microstructure

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Figure 6

Macrostructure for the set of papers concerning computer integrated manufacturing

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Figure 7

Top four equivalence classes extracted from the set of papers concerning computer integrated manufacturing. (The words shown here are those obtained after stemming.)

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Figure 8

Microstructure for a paper abstract in the set of papers pertaining to computer integrated manufacturing

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Figure 9

Summarization output for exemplar set of papers: major topics and their background information

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