With the advent of the era of big data in electric power, technologies based on artificial intelligence, cloud computing, and the Internet of Things have been widely used in the electric power industry. For the innovation and development of various industries, knowledge map technology has become a new driving force, but there are few studies on knowledge map in the electric power field. This paper focuses on the electric power industry, builds a knowledge map with the goal of integrating knowledge resources in the industry, and provides knowledge applications in the form of scene-based professional knowledge search, accurate knowledge push, and decision support, serving practitioners, corporate organizations and industry decision makers. This article will share some exploration and practice of knowledge map application in the power industry.
Today's sharing revolves around the following four parts:
1. Construction of power knowledge system
2. Electric power knowledge map construction
3. Application scenarios
4. Landing application and experience
Sharing guest｜Zhang Taoying, editor and reviewer of Da Media Investment Group Co., Ltd.
Editing｜Hou Hongmei
Production Community｜DataFun
01/Electric power knowledge system construction
In the process of building a knowledge map, the first thing we need to do is knowledge modeling.
1. Power knowledge data
Power industry data is different from power knowledge data. Power industry data includes power operation data, marketing data and management data, which are data generated by power production; power knowledge data is aimed at serving power industry production, and is scientific, systematic, open, and verifiable data formed in power production . Why do we say that the right can be confirmed? Because from the perspective of publishing, what we do is the production and dissemination of knowledge, so if we want to share the disseminated knowledge, we must determine the copyright ownership of the knowledge