Abstract
The application of data mining technology in power field mainly focuses on the application of power defect text and dispatching text. However, the power operation and maintenance data contains a lot of information about power equipment suppliers. Taking the operation and maintenance text involving power equipment suppliers as an example, this paper summarizes the theme of operation and maintenance text and studies the evaluation model of power equipment suppliers. The next sentence prediction analysis model of single round dialogue text based on transformer bidirectional encoder prediction and cosine similarity weighting is proposed, which can effectively divide the topic of dialogue text. Aiming at the semantic richness and complexity of power operation and maintenance text, a supplier evaluation model based on text emotion analysis is proposed. Based on the expansion of the entries and attributes of the existing power ontology dictionary, the dialogue emotion analysis rules are established to realize the normal evaluation of power equipment suppliers.
Highlights
At present, the basic requirement of ubiquitous power Internet of things construction is to realize business collaboration and data connectivity
A large proportion of unstructured data accumulated in the construction and development of smart grid, as an important part of power big data, is of great significance to the intelligent development of power grid
Erefore, in this paper, the text intelligent mining in the power field is taken as the research object, the power text is analyzed and processed by using natural language processing technology, effective information is obtained, and support for the evaluation of power equipment suppliers is provided
Summary
The basic requirement of ubiquitous power Internet of things construction is to realize business collaboration and data connectivity. Intelligent mining of unstructured text data of power grid is a hot and difficult problem. E intelligent mining of unstructured text data information in power field can use natural language processing technology [2]. E application of natural language processing technology in the field of electric power mostly focuses on text classification and knowledge Atlas, and there is little exploration in the direction of emotion analysis and information retrieval. Erefore, in this paper, the text intelligent mining in the power field is taken as the research object, the power text is analyzed and processed by using natural language processing technology, effective information is obtained, and support for the evaluation of power equipment suppliers is provided. Ban and Ning [13] established a manually labeled open-source power business intention identification data set for power business dialogue, which laid a foundation for the verification of power dialogue text classification model
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
