Research on Intelligent Power Marketing Inspection Model Based on Knowledge Graph

The traditional topic-based auditing model lacks the ability of multi-object and multi-abnormal correlation auditing, which makes it impossible to solve the multi-scenario and multi-factor correlation-based auditing problem. This paper designs an intelligent power marketing audit model based on a kn...

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Bibliographic Details
Published in:Scientific programming 2022-10, Vol.2022, p.1-8
Main Authors: Wang, Jinghua, Chen, Bingxu, Wang, Yue, Xu, Zihan, Zhao, Wanru
Format: Article
Language:English
Subjects:
Annotations
Audits
Coders
Construction
Copying
Customer services
Data analysis
Efficiency
Electric power
Electricity
Electricity distribution
Information management
Information systems
Inspection
Knowledge
Knowledge representation
Marketing
Natural language processing
Power supply
Semantics
Supervision
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Summary:The traditional topic-based auditing model lacks the ability of multi-object and multi-abnormal correlation auditing, which makes it impossible to solve the multi-scenario and multi-factor correlation-based auditing problem. This paper designs an intelligent power marketing audit model based on a knowledge graph. First, an entity identification and relationship extraction method for power marketing business based on NLP (natural language processing) and sequence annotation technology is proposed, and the description content is imported into the knowledge graph database; then, semantic disambiguation and knowledge are carried out by using bidirectional encoder representation from transformers (BERT). Link to build a knowledge map of business audit rules: Finally, an experimental analysis is carried out by taking the copying and receiving business with a large business volume in the marketing audit work as an example, and it is verified that the proposed model can effectively improve the information analysis ability and the audit accuracy of the audit work.
ISSN:1058-9244
1875-919X
DOI:10.1155/2022/7116988