从数据驱动的角度来看,商业意图和网络切片相关性数据集
Jie Li1, Sai Zou2, Yanglong Sun3
1College of Big Data and Information Engineering, Guizhou University, Gui Yang, 550000, China.
Scientific data
|March 11, 2025
概括
本研究介绍了商业意图和网络切片相关数据集 (BINS),以解决基于意图的网络 (IBN) 中意图提取数据的缺乏. 通过将业务意图与网络切片相关联,BINS促进了下一代网络的研究.
科学领域:
- 计算机科学 计算机科学
- 网络工程 网络工程
- 数据科学数据科学数据科学
背景情况:
- 基于意图的网络 (IBN) 通过用户意图自动化网络配置.
- 准确的意图提取对IBN至关重要,但缺乏足够的公共数据集.
- 大数据趋势需要数据驱动的研究,以便未来的网络调查.
研究的目的:
- 引入商业意图和网络切片相关数据集 (BINS).
- 支持下一代网络和基于意图的网络研究.
- 提供注释数据,将业务意图与网络切片相关联.
主要方法:
- 创建数据集,包括业务意图描述和注释意图数据.
- 业务意图和网络切片之间的相关性分析.
- 使用自然语言处理 (NLP) 和命名实体识别 (NER) 验证数据质量.
- 使用DataProfiler进行第三方数据分析和验证.
主要成果:
- BINS数据集已成功创建和验证数据质量和可靠性.
- 数据集包含用户业务意图描述,注释意图数据,以及它们与网络切片的相关性.
- 通过严格的数据验证流程证实了BINS数据集的可靠性.
结论:
- BINS数据集是推动基于意图的网络研究的宝贵资源.
- 它解决了在网络意图识别中对数据的关键需求.
- BINS将帮助研究人员和从业人员探索应用互动和相关技术.
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