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English(EN) Leveraging contextual events on structure-aware next activity prediction

新方法使用实例图和GNN进行更好的流程预测

研究人员开发了一种利用实例图和图神经网络进行流程中下一次活动预测的新方法。该方法显式编码了上下文信息,例如流程执行期间的环境条件,而这在以前的方法中是一个限制。在真实事件日志上的实验表明,结合这些上下文流程实例可以提高预测性能。 AI

影响 这项研究通过更好地利用上下文数据,有望实现更准确的流程监控和预测。

排序理由 该集群包含一篇在arXiv上发表的研究论文,详细介绍了一种新的流程预测方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新方法使用实例图和GNN进行更好的流程预测

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该集群包含一篇在arXiv上发表的研究论文,详细介绍了一种新的流程预测方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Alessandro Mele, Claudia Diamantini, Domenico Potena ·

    利用结构感知型下个活动预测中的上下文事件

    arXiv:2609.08622v1 Announce Type: cross Abstract: Predictive process monitoring aims at forecasting various aspects of running processes. Among the different tasks, next activity prediction represents the most extensively investigated. However, only a limited number of existing a…