From Low-Level Events to Activities -- A Session-Based Approach (Extended Version)
Massimiliano de Leoni, Safa Dundar

TL;DR
This paper introduces a session-based abstraction technique for process mining that simplifies event data into high-level activities using clustering and visualization, improving interpretability with minimal domain knowledge.
Contribution
It proposes a novel session-based abstraction method combining automatic clustering and visualization, requiring limited domain knowledge, to enhance process mining interpretability.
Findings
Effective abstraction of event sequences into high-level activities.
Improved clarity and usefulness of process models for stakeholders.
Validated on two complex case studies demonstrating benefits.
Abstract
Process-Mining techniques aim to use event data about past executions to gain insight into how processes are executed. While these techniques are proven to be very valuable, they are less successful to reach their goal if the process is flexible and, hence, events can potentially occur in any order. Furthermore, information systems can record events at very low level, which do not match the high-level concepts known at business level. Without abstracting sequences of events to high-level concepts, the results of applying process mining (e.g., discovered models) easily become very complex and difficult to interpret, which ultimately means that they are of little use. A large body of research exists on event abstraction but typically a large amount of domain knowledge is required to be fed in, which is often not readily available. Other abstraction techniques are unsupervised, which give…
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Taxonomy
TopicsBusiness Process Modeling and Analysis · Service-Oriented Architecture and Web Services · Data Quality and Management
