面向业务流程管理自动化的条件句识别与拆分
Recognizing and Splitting Conditional Sentences for Automation of Business Processes Management
摘要：
业务流程管理（BPM）是一门负责发现、分析、重新设计、监视和控制业务流程的学科。BPM最重要的任务之一是从文本文档中发现业务流程并对其建模。在本文中，我们提出了我们的系统，解决了一个端到端的问题，包括1）从技术文档中识别条件句，2）找到边界，从每个条件句中提取条件和结果子句，3）将结果子句分类为Action或Consequence，这有助于在我们的业务流程模型中自动生成新的步骤。我们创建了一个新的数据集，三个模型解决了这个问题。我们的最佳模型在使用精确匹配度量提取条件、动作和结果子句时，分别获得了非常有希望的精度、召回率和F1结果，分别为83.82、87.84和85.75。
英文摘要：
Business Process Management (BPM) is the discipline which is responsible for management of discovering, analyzing, redesigning, monitoring, and controlling business processes. One of the most crucial tasks of BPM is discovering and modelling business processes from text documents. In this paper, we present our system that resolves an end-to-end problem consisting of 1) recognizing conditional sentences from technical documents, 2) finding boundaries to extract conditional and resultant clauses from each conditional sentence, and 3) categorizing resultant clause as Action or Consequence which later helps to generate new steps in our business process model automatically. We created a new dataset and three models solve this problem. Our best model achieved very promising results of 83.82, 87.84, and 85.75 for Precision, Recall, and F1, respectively, for extracting Condition, Action, and Consequence clauses using Exact Match metric.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
