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

• Published in: Journal of Zhejiang University. A. Science Vol. 6; no. 11; pp. 1258 - 1267
• Main Authors: Shi-yan, Ou, Khoo Christopher, S. G., Goh Dion, H.
• Format: Journal Article
• Language: English
• Published: Division of lnformation Studies, School of Communication & Information, Nanyang Technological University, 639798, Singapore 01.11.2005
• Subjects: 信息系统; 多文件摘要; 数字图书馆; 框架结构; 自动化技术; Automatic multi-document summarization; Text summarization; Variable-based framework; Digital library
• ISSN: 1673-565X; 1862-1775
• DOI: 10.1631/jzus.2005.A1258

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.