Process descriptions are used to create products and deliver services. To lead better processes and services, the first step is to learn a process model. Process discovery is such a technique which can automatically extract process models from event logs. Although various discovery techniques have been proposed, they focus on either constructing formal models which are very powerful but complex, or creating informal models which are intuitive but lack semantics. In this work, we introduce a novel method that returns hybrid process models to bridge this gap. Moreover, to cope with today's big event logs, we propose an efficient method, called f-HMD, aims at scalable hybrid model discovery in a cloud computing environment. We present the detailed implementation of our approach over the Spark framework, and our experimental results demonstrate that the proposed method is efficient and scalable.

中文翻译：

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云计算环境中混合流程模型的可扩展发现

流程描述用于创建产品和提供服务。要引领更好的流程和服务，第一步是学习流程模型。流程发现是一种可以从事件日志中自动提取流程模型的技术。尽管已经提出了各种发现技术，但它们要么专注于构建非常强大但复杂的形式模型，要么专注于创建直观但缺乏语义的非正式模型。在这项工作中，我们引入了一种返回混合过程模型的新方法来弥合这一差距。此外，为了应对当今的大事件日志，我们提出了一种称为 f-HMD 的有效方法，旨在在云计算环境中进行可扩展的混合模型发现。我们展示了我们的方法在 Spark 框架上的详细实现，