Power skill training knowledge base construction based on knowledge map and improved FP-Growth

Abstract

This paper designs the power skill training knowledge base model based on the knowledge mapping, which includes two levels and four basic elements, based on the analysis of the characteristics of power grid skill training. An improved FP-Growth algorithm considering interest value coefficient is proposed, which can filter the invalid learning access out of the frequent items. In this paper, the power skill training knowledge base is preliminarily established. The learning data of some trainees in the knowledge base are selected to update the resource association relationship. The updated training knowledge base enriches the resource association relationship, realizing the resource mining and integration among multiple posts and capabilities. The power skill training knowledge base can provide an intelligent and personalized skill training platform for power technical staff, to improve the skill level of staff, and further ensure the safe and reliable operation of the power grid.