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Generating synthetic positive and negative business process traces through abduction
Knowledge and Information Systems ( IF 2.7 ) Pub Date : 2019-06-20 , DOI: 10.1007/s10115-019-01372-z
Daniela Loreti , Federico Chesani , Anna Ciampolini , Paola Mello

As recent years have seen the rise of a new discipline commonly addressed as process mining, focused on the management of business processes, two tasks have gained increasing attention in research: process discovery and compliance monitoring. In both these fields, the demand for event log benchmarks with predefined characteristics has determined the design of various methodologies and tools for synthetic log generation. However, artificially created as well as real-life logs often contain positive examples only (i.e. process instances deemed as compliant w.r.t. the model), while the presence of negative process instances (i.e. non-compliant traces) can be crucial to correctly evaluate the performance and robustness of a novel process discovery or conformance checking technique. In this work, we investigate positive and negative trace generation in case of both declarative and procedural model specifications and we present our abduction-based approach to log synthesis. The theoretical study is concretely applied in a software prototype for log generation, which takes as input a declarative or structured workflow model and emits logs containing positive and negative traces. The approach provides both a highly expressive notation for the description of the business model and the ability to generate logs with various customizable features. The final comparative study of other existing log generators reveals several advantages of the proposed approach and draws the direction of future improvements.

中文翻译:

通过绑架生成综合的正面和负面业务流程痕迹

随着近年来所看到的一门新兴学科的崛起,共同寻址过程挖掘,专注于业务流程的管理,两项任务已经获得了越来越多的关注研究:流程发现合规性监控。在这两个领域中,对具有预定义特征的事件日志基准的需求已确定了用于合成日志生成的各种方法和工具的设计。但是,人工创建的日志和实际日志通常仅包含肯定示例(即,与该模型兼容的流程实例),而存在否定日志流程实例(即不合规的跟踪)对于正确评估新型流程发现或一致性检查技术的性能和健壮性至关重要。在这项工作中,我们研究了在声明性和程序性模型规范的情况下正向和负向轨迹的生成,并提出了基于绑架的日志合成方法。该理论研究具体应用于日志生成的软件原型中,该原型以声明性或结构化的工作流模型为输入,并发出包含正迹线和负迹线的日志。该方法既为业务模型的描述提供了高度表达的符号,又为具有各种可自定义功能的日志生成提供了能力。
更新日期:2019-06-20
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