| Title |
Gen2Vec: Deep Learning based Distributed Representation Framework of Words and Documents for Diagnostic Services of Power Generation Facility |
| Authors |
황명하(Myeong-Ha Hwang) ; 이인태(In-Tae Lee) ; 채창훈(Chang-Hun Chae) ; 정남준(Nam-Joon Jung) |
| DOI |
https://doi.org/10.5370/KIEE.2020.69.12.1808 |
| Keywords |
Deep Learning; Natural Language Processing; Power Generation; Diagnostic Service; Text Mining; Framework |
| Abstract |
Since the advent of deep learning technology, research and development have been conducted in various fields. In particular, deep learning technology related to embedding that vectorizes the similarity between words has been attracting attention in the natural language processing sector. However, this technology has not been applied to the electric power industry, and no corresponding service frameworks have been developed. Moreover, thousands of knowledge documents produced by electric generator operation experts have been collected for about 20 years by Korea Electric Power Corporation, but they have rarely been applied to electric generator operation. Therefore, this report proposes Gen2Vec, a search engine-based framework for operating power plant using deep learning technology. Gen2Vec can be the core engine of the knowledge system for power plant operators and can be used in search and chatbot services for power plant operation programs and new employee education. |