Knowledge Mining for Defining Systemic Engineering Practices

This paper addresses the problem on generating knowledge graphs from research papers related to wildfires, and their impacts on the electrical grid infrastructure. A novel framework based on part-of-speech tagging, word frequency statistics, and document clustering is proposed for extracting information and generating knowledge graphs from a selfcurated corpus of wildfire-related research work abstracts. The proposed method is capable of capturing a wide range of insightful information from the self-generated domain-specific corpus. Systemic engineering practices, such as strategies for wildfire mitigation by electric utilities has been included as a case study in this paper. An application of the research is implemented for simulating the management and mitigation of wildfires by electric utilities in California.