3-D Networks for Mining Knowledge from Energy Policy Literatures

Abstract:

Data mining is a hot research topic over the last twenty years or more. In recent decades, network graphs that have represented knowledge of a focus topic have gained increasing attention. These maps include term network, concept map, topic map or knowledge map. A concept map is one of the visualization tools to show the relationships among concepts. It is a graphical tool for organizing and representing knowledge. Global warming poses a grave threat to the world’s ecological system. Economic development has led to a huge increase in energy demand and therefore energy efficiency and saving has become a key issue for most countries. In many countries, they tried hard to find renewable and sustainable energy supplies and sources. This study tries to analyze trends of energy policy literatures from the international literature database within last three years to be visualized in 3-D concept map layouts; besides, measuring keyword relation linkages though control variables of concept maps, such as size of node, linkage, relations and dynamic figure layout, are the main contributions to academics. This research adapts an IP (integer programming) model to maximize relation linkages for each node among a term network. The more linkages, the more useful information offered for mining knowledge from a term network. The 3-D concept map was demonstrated. Future research suggests applying this approach to other research literatures from international literature databases.

• Periodical: Applied Mechanics and Materials (Volume 310)
• Pages: 572-575
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.310.572
• Online since: February 2013
• Authors: Sen Po Wu, Zih Ping Ho, Jung Hui Chiu
• Keywords: 3-D Networks, Concept Maps, Graphic Added Literature Analyzer, Text Mining, Visualization Tools

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