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

作     者：KHOO Christopher S.G. GOH Dion H. 

作者机构：Division of Information Studies School of Communication & Information Nanyang Technological University 639798 SingaporeDivision of Information Studies School of Communication & Information Nanyang Technological University 639798 Singapore 

出 版 物：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 (浙江大学学报（英文版）A辑（应用物理与工程）)

年 卷 期：2005年第6卷第11期

页      面：1258-1267页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Text summarization Automatic multi-document summarization Variable-based framework Digital library 

摘      要：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.