原生直接跟随运算符
Native Directly Follows Operator
摘要：
典型的遗留信息系统将数据存储在关系数据库中。流程挖掘是一门研究学科，它分析这些数据以获得对流程的洞察。许多不同的过程挖掘技术可以应用于数据。在当前技术中，XES事件日志用作分析的基础。然而，由于XES事件日志的静态特性，我们需要为每个流程挖掘问题创建一个XES文件，这导致了开销和可扩展性。作为替代方案，人们尝试使用所谓的中间结构直接在数据源上执行过程挖掘。在以前的工作中，我们研究了通过在数据库上执行基本SQL查询来在源数据上构建中间结构的方法。但是，SQL查询中的嵌套表单可能会导致数据库端的性能问题。因此，在本文中，我们提出了一个原生的SQL操作直接进程发现关系数据库。我们为中间结构的最简单形式定义了一个本地操作符，称为“直接跟随关系”。该方法已与大事件数据进行了评估，实验结果表明，它的执行速度比最先进的数据库方法。
英文摘要：
Typical legacy information systems store data in relational databases. Process mining is a research discipline that analyzes this data to obtain insights into processes. Many different process mining techniques can be applied to data. In current techniques, an XES event log serves as a basis for analysis. However, because of the static characteristic of an XES event log, we need to create one XES file for each process mining question, which leads to overhead and inflexibility. As an alternative, people attempt to perform process mining directly on the data source using so-called intermediate structures. In previous work, we investigated methods to build intermediate structures on source data by executing a basic SQL query on the database. However, the nested form in the SQL query can cause performance issues on the database side. Therefore, in this paper, we propose a native SQL operator for direct process discovery on relational databases. We define a native operator for the simplest form of the intermediate structure, called the "directly follows relation". This approach has been evaluated with big event data and the experimental results show that it performs faster than the state-of-the-art of database approaches.
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