Using Contextual Text Mining and Ontology Methods to Establish a Novel Technology Trend and Associative Analysis Framework for Sustainable Energy Development in Taiwan

In 2015, the United Nations proposed 17 Sustainable Development Goals, SDGs, as the guidelines for all countries in the world to promote sustainable development before 2030. Government Research Bulletin (GRB), the research projects and technical reports sponsored by government, which has long-term, numerous, complete research method, technology development and policy analysis information in Taiwan. Therefore, it is an important and effective way to explore SDG-related information from a large amount of GRB text. In this paper, a novel technologies trend and associative analysis framework which uses contextual text mining and ontology methods is proposed and applied to SDG 7, which "Affordable and Clean Energy". First, we integrate dictionary-based method and semantic textual similarity analysis algorithm to obtain a SDG 7 classifier which can exactly and quickly classify a large amount number of GRB text to SDG 7. Then, two major SDG 7 analysis procedures based on the classification results are implemented. One is using contextual text mining algorithm to obtain energy technologies trend information. The other is adopting ontology method to establish energy technologies associative analysis concept map. According to the analysis results mentioned above, we are able to efficiently incorporate the energy technology with long-term trend, energy technology associative information, and the most influential authors on the specify energy technology in order to generate a global strategy for continuous improvement in Taiwan.