Similarity Determination in Activity Sequences – A Supportive Framework

An increasing number of information systems support their users by helping them in reusing existing knowledge and experience. Often this is done by retrieving similar instances like similar documents, similar process executions or similar persons. While the recommendations use similarity as central concept, the selection of a suitable measure is often done by intuition. This paper introduces a framework that supports the application engineer in selecting and configuring a suitable similarity measure. The requirements of the intended framework are gathered before the architectural implications are detailed. The resulting framework is applied in a case study in which project performance prediction is to be supported by the similarity of the projects’ activity sequences. The results show the framework’s utility by allowing a comparably simple configuration to yield a considerable support in selecting and configuring a suitable similarity measure

Partial-order-based process mining: a survey and outlook

The field of process mining focuses on distilling knowledge of the (historical) execution of a process based on the operational event data generated and stored during its execution. Most existing process mining techniques assume that the event data describe activity executions as degenerate time intervals, i.e., intervals of the form [t, t], yielding a strict total order on the observed activity instances. However, for various practical use cases, e.g., the logging of activity executions with a nonzero duration and uncertainty on the correctness of the recorded timestamps of the activity executions, assuming a partial order on the observed activity instances is more appropriate. Using partial orders to represent process executions, i.e., based on recorded event data, allows for new classes of process mining algorithms, i.e., aware of parallelism and robust to uncertainty. Yet, interestingly, only a limited number of studies consider using intermediate data abstractions that explicitly assume a partial order over a collection of observed activity instances. Considering recent developments in process mining, e.g., the prevalence of high-quality event data and techniques for event data abstraction, the need for algorithms designed to handle partially ordered event data is expected to grow in the upcoming years. Therefore, this paper presents a survey of process mining techniques that explicitly use partial orders to represent recorded process behavior. We performed a keyword search, followed by a snowball sampling strategy, yielding 68 relevant articles in the field. We observe a recent uptake in works covering partial-order-based process mining, e.g., due to the current trend of process mining based on uncertain event data. Furthermore, we outline promising novel research directions for the use of partial orders in the context of process mining algorithms

A basic tool for the modeling of Marked-Controlled Reconfigurable Petri Nets

In previous studies, we have introduced marked-controlled net rewriting systems and a subclass of these called marked-controlled reconfigurable Petri nets. In a marked-controlled net rewriting system, a system configuration is described as a Petri net, and a change in configuration is described as a graph rewriting rule. A marked-controlled reconfigurable Petri net is a marked-controlled net rewriting system where a change in configuration amounts to a modification in the flow relations of the places in the domain of the involved rule in accordance with this rule, independently of the context in which this rewriting applies. In both models, the enabling of a rule not only depends on the net topology, but also depends on the net marking according to control places. Even though the expressiveness of Petri nets and marked-controlled reconfigurable Petri nets is the same, with marked-controlled reconfigurable Petri nets, we can easily and directly model concurrent and distributed systems that change their structure dynamically. In this article, we present MCReNet, a tool for the modeling and verification of marked-controlled reconfigurable Petri nets

Exploring the Integration of Agent-Based Modelling, Process Mining, and Business Process Management through a Text Analytics–Based Literature Review

Agent-based modelling and business process management are two interrelated yet distinct concepts. To explore the relationship between these two fields, we conducted a systematic literature review to investigate existing methods and identify research gaps in the integration of agent-based modelling, process mining, and business process management. Our search yielded 359 research papers, which were evaluated using predefined criteria and quality measures. This resulted in a final selection of forty-two papers. Our findings reveal several research gaps, including the need for enhanced validation methods, the modelling of complex agents and environments, and the integration of process mining and business process management with emerging technologies. Existing agent-based approaches within process mining and business process management have paved the way for identifying the validation methods for performance evaluation. The addressed research gaps primarily concern validation before delving deeper into specific research topics. These include improved validation methods, modelling of complex agents and environments, and a preliminary exploration of integrating process mining and business process management with emerging technologies

Process discovery algorithms using numerical abstract domains

The discovery of process models from event logs has emerged as one of the crucial problems for enabling the continuous support in the life-cycle of an information system. However, in a decade of process discovery research, the algorithms and tools that have appeared are known to have strong limitations in several dimensions. The size of the logs and the formal properties of the model discovered are the two main challenges nowadays. In this paper we propose the use of numerical abstract domains for tackling these two problems, for the particular case of the discovery of Petri nets. First, numerical abstract domains enable the discovery of general process models, requiring no knowledge (e.g., the bound of the Petri net to derive) for the discovery algorithm. Second, by using divide and conquer techniques we are able to control the size of the process discovery problems. The methods proposed in this paper have been implemented in a prototype tool and experiments are reported illustrating the significance of this fresh view of the process discovery problem.Peer ReviewedPostprint (author’s final draft

Semantic business process management: scaling up the management of business processes

Business Process Management (BPM) aims at supporting the whole life-cycle necessary to deploy and maintain business processes in organisations. Despite its success however, BPM suffers from a lack of automation that would support a smooth transition between the business world and the IT world. We argue that Semantic BPM, that is, the enhancement of BPM with Semantic Web Services technologies, provides further scalability to BPM by increasing the level of automation that can be achieved. We describe the particular SBPM approach developed within the SUPER project and we illustrate how it contributes to enhancing existing BPM solutions in order to achieve more flexible, dynamic and manageable business processes

Blockchain logging for process mining: a systematic review

Considerable progress was forcasted for collaborative business processes with the rise of blockchain programmable platforms. One of the saliant promises was auditable traces of business process execution, but practically that has posed challenges specially with regard to blockchain logs’ structure who turned out to be inadequate for process mining techniques. Approaches to answer this issue have started to emerge in the literature, some focusing on the creation process of event logs and others dealing with their retrieval from the blockchain. This work outlines the generic steps required to solve these challenges and analyzes findings in these approaches with a consideration for efficiency and future research directions