在电力B2B部门使用的新型电子商务推系统的开发和应用
Wenjun Meng1,2, Lili Chen3, Zhaomin Dong4
1School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China.
Frontiers in big data
|August 15, 2024
概括
这项研究引入了电力行业的新推引擎,克服了数据稀疏和交易不频繁等挑战. 这种新系统通过整合各种数据来提供更相关的产品建议来增强企业对企业 (B2B) 电子商务.
科学领域:
- * 计算机科学 计算机科学
- *电子商务技术 *电子商务技术
- * 工业系统工程 工业系统工程
背景情况:
- * 传统的电子商务推系统对于电力行业独特的B2B交易特点是不够的.
- * 挑战包括不频繁,高风险的交易,长时间的决策周期和稀少的数据,阻碍有效的数字商业.
- * 现有的系统无法满足专业化工业市场的特定需求.
研究的目的:
- * 开发一个专门为电力行业的B2B电子商务环境设计的新型推引擎.
- * 解决传统系统在处理稀疏数据和不频繁,长周期交易方面的局限性.
- * 提高专业工业部门建议的准确性和相关性.
主要方法:
- * 开发了用于处理有限数据和数据预处理技术的算法增强,以丰富稀疏的数据集.
- * 引入了一项方法创新,整合了多维数据:用户电子商务活动,产品细节和非招标信息.
- * 采用先进的机器学习技术来解释数据和生成建议.
主要成果:
- * 新型推引擎在电力行业的背景下,与传统模型相比,显著改进.
- * 该系统有效地处理企业对企业 (B2B) 交易的低频率和长周期性质.
- * 增强的数据处理和整合导致了更准确和更相关的产品建议.
结论:
- *开发的推引擎提供了一个强大的和有效的工具,以促进电力部门的B2B交易.
- * 这项研究成功地解决了工业电子商务推系统的独特挑战.
- * 这项工作提供了一个可转移的蓝图,用于将推引擎适应具有类似B2B特征的其他行业.
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