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Received: 2005-08-05

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Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.11 P.1258-1267


Constructing a taxonomy to support multi-document summarization of dissertation abstracts

Author(s):  OU Shi-yan, KHOO Christopher S.G., GOH Dion H.

Affiliation(s):  Division of Information Studies, School of Communication & Information, Nanyang Technological University, 639798, Singapore

Corresponding email(s):   pg00096125@ntu.edu.sg, assgkhoo@ntu.edu.sg, ashlgoh@ntu.edu.sg

Key Words:  Text summarization, Automatic multi-document summarization, Variable-based framework, Digital library

OU Shi-yan, KHOO Christopher S.G., GOH Dion H.. Constructing a taxonomy to support multi-document summarization of dissertation abstracts[J]. Journal of Zhejiang University Science A, 2005, 6(11): 1258-1267.

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This paper reports part of a study to develop a method for automatic multi-document summarization. The current focus is on dissertation abstracts in the field of sociology. The summarization method uses macro-level and micro-level discourse structure to identify important information that can be extracted from dissertation abstracts, and then uses a variable-based framework to integrate and organize extracted information across dissertation abstracts. This framework focuses more on research concepts and their research relationships found in sociology dissertation abstracts and has a hierarchical structure. A taxonomy is constructed to support the summarization process in two ways: (1) helping to identify important concepts and relations expressed in the text, and (2) providing a structure for linking similar concepts in different abstracts. This paper describes the variable-based framework and the summarization process, and then reports the construction of the taxonomy for supporting the summarization process. An example is provided to show how to use the constructed taxonomy to identify important concepts and integrate the concepts extracted from different abstracts.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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