Application of text mining technology in power data prediction
Konferenz: CIBDA 2022 - 3rd International Conference on Computer Information and Big Data Applications
25.03.2022 - 27.03.2022 in Wuhan, China
Tagungsband: CIBDA 2022
Seiten: 4Sprache: EnglischTyp: PDF
Autoren:
Guo, Jian (College of Architecture and Civil Engineering, Qiqihar University, Qiqihar, China)
Guo, Wu (College of Communication and Electronic Engineering, Qiqihar University, Qiqihar, China)
Inhalt:
This paper analyses the main research methods of power text mining technology in detail, and discusses the research hotspots of power text named entity recognition and named entity relationship extraction based on machine learning and deep learning. On this basis, the limited Boltzmann machine is further used to predict the power data. The test results show that the analysis of power text features in this paper is accurate, can effectively analyse the key text information, and the prediction results meet the requirements.