A Modeling and Analysis Framework for Knowledge System Based on Meta-Network Approach

摘要：

　　Nowadays some online research platforms (e.g., Web of Science or IEEE Xplore) provide bibliographic content and tools to access, analyze, and manage the worlds leading journals and conference proceedings in sciences, social science, arts, and humanities.However, when facing increasingly mass literature, its very difficult for researchers to effectively and systematically acquire the knowledge structure about a particular topic by using traditional literature reviewing method.Therefore we need explore new knowledge discovery tools for knowledge representation in an effective and efficient way.This paper proposes a knowledge system meta-network model by identifying the concepts representing entities and relationships from bibliometric data, and a methodology framework for meta-network modeling and analysis by using integrated techniques, including text mining, network text analysis, social network analysis, longitudinal network analysis and visualization.Case study using the Web of Science database as data source, explores the knowledge structure and interdisciplinary cooperation mode, as well as hot topics evolution in the field of World Trade Web.

关键词： knowledge system,meta-network,text mining network text analysis world trade web

作者: Xiao Liu Jun Wang

作者单位: School of Management, Jinan University (Guangzhou), China School of Economics, Jinan University (Guangzhou), China

会议类型: 国际会议

会议名称: The Thirteenth Wuhan International Conference on E-Business(第十三届武汉电子商务国际会议)(WHICEB2014)

会议地点: 武汉

会议语种:英文

页码: 196-204

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）