用三角不等式加速流程后缀比对，不损失精度且大幅提速。
Efficient Distance Pruning for Process Suffix Comparison in Prescriptive Process Monitoring
- 基于优化的枢纽点和三角不等式构建距离上下界，提前剪枝冗余计算。
- 在大规模日志下显著降低运行时间，且可完全并行化处理。
- 适用于需要高精度流程推荐的工业系统，如制造、医疗监控。
规范性流程监控旨在通过分析正在进行案例的可能延续路径，推荐能改进流程结果的操作。其主要障碍在于大规模后缀比对带来的高昂计算成本，该成本随日志规模迅速增长。本文提出一种高效检索方法，利用三角不等式：通过一组优化的枢纽点定义距离上下界，实现冗余比较的剪枝。该方法显著降低运行时间，且完全可并行化。关键优势在于剪枝是精确的——所检索的后缀与穷举比对结果完全一致，从而保证了准确性。结果表明，基于度量的剪枝可有效加速后缀比较，支持可扩展的规范性系统。
原文摘要 · Abstract (English)
Prescriptive process monitoring seeks to recommend actions that improve process outcomes by analyzing possible continuations of ongoing cases. A key obstacle is the heavy computational cost of large-scale suffix comparisons, which grows rapidly with log size. We propose an efficient retrieval method exploiting the triangle inequality: distances to a set of optimized pivots define bounds that prune redundant comparisons. This substantially reduces runtime and is fully parallelizable. Crucially, pruning is exact: the retrieved suffixes are identical to those from exhaustive comparison, thereby preserving accuracy. These results show that metric-based pruning can accelerate suffix comparison and support scalable prescriptive systems.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。