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Evaluation Model of Power Operation and Maintenance Based on Text Emotion Analysis
Author(s) -
Wei Wan,
Yuanlong Liu,
Xingwang Han,
Huijian Wang
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/2824689
Subject(s) - computer science , power (physics) , encoder , sentence , cosine similarity , transformer , ontology , data mining , information retrieval , artificial intelligence , reliability engineering , natural language processing , engineering , electrical engineering , pattern recognition (psychology) , philosophy , physics , epistemology , quantum mechanics , voltage , operating system
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.

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