Research on Constructing a Knowledge Graph for Risk-Aware Electricity Marketing Events

DOI

10.2991/978-94-6463-304-7_71How to use a DOI?

Keywords

Electricity Marketing; Risk Perception; Event Knowledge Graph

Abstract

Considering the diverse evolution of electricity marketing business requirements alongside the advancement of socioeconomic development and deepening market reforms, the effective utilization of extensive and dynamically changing data in electricity marketing has presented both opportunities and challenges for marketing risk management. Thus, this paper, commencing from the needs of risk perception in electricity marketing events, proposes an innovative approach using a novel method of integrating marketing data – the Event Knowledge Graph. Building on this, the paper explores the model and construction process of the electricity marketing event knowledge graph, as well as the methodological pathway for conducting risk perception based on this knowledge graph. The objective is to facilitate knowledge-based management of electricity marketing events and offer support for risk awareness and regulatory decision-making in this context.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Gang Sun
AU  - Wangying Jin
AU  - Shiyu Xu
AU  - Liuxin Yang
AU  - Wanjing Song
PY  - 2023
DA  - 2023/12/04
TI  - Research on Constructing a Knowledge Graph for Risk-Aware Electricity Marketing Events
BT  - Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
PB  - Atlantis Press
SP  - 677
EP  - 688
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-304-7_71
DO  - 10.2991/978-94-6463-304-7_71
ID  - Sun2023
ER  -