Josep Carmona

Process Mining Manifesto

Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes.

Elastic Circuits

Elasticity in circuits and systems provides tolerance to variations in computation and communication delays. This paper presents a comprehensive overview of elastic circuits for those designers who are mainly familiar with synchronous design. Elasticity can be implemented both synchronously and asynchronously, although it was traditionally more often associated with asynchronous circuits. This paper shows that synchronous and asynchronous elastic circuits can be designed, analyzed, and optimized using similar techniques. Thus, choices between synchronous and asynchronous implementations are localized and deferred until late in the design process.

A fresh look at precision in process conformance

Process Conformance is a crucial step in the area of Process Mining: the adequacy of a model derived from applying a discovery algorithm to a log must be certified before making further decisions that affect the system under consideration. Among the different conformance dimensions, in this paper we propose a novel measure for precision, based on the simple idea of counting these situations were the model deviates from the log. Moreover, a log-based traversal of the model that avoids inspecting its whole behavior is presented. Experimental results show a significant improvement when compared to current approaches for the same task. Finally, the detection of the shortest traces in the model that lead to discrepancies is presented.

A Region-Based Algorithm for Discovering Petri Nets from Event Logs

The paper presents a new method for the synthesis of Petri nets from event logs in the area of Process Mining. The method derives a bounded Petri net that over-approximates the behavior of an event log. The most important property is that it produces a net with the smallest behavior that still contains the behavior of the event log. The methods described in this paper have been implemented in a tool and tested on a set of examples.

New Region-Based Algorithms for Deriving Bounded Petri Nets

The theory of regions was introduced in the early nineties as a method to bridge state and event-based models. This paper tackles the problem of deriving a Petri net from a state-based model, using the theory of regions. Some of the restrictions required in the traditional approach are dropped in this paper, together with significant extensions that make the approach applicable in new scenarios. One of these scenarios is Process Mining, where accepting (discovering) additional behavior in the synthesized Petri net is sometimes valued. The algorithmic emphasis used in this paper contributes to the demystification of the theory of regions as been only a good theoretical exercise, opening the door for its application in the industrial domain.

Alignment based precision checking

Most organizations have process models describing how cases need to be handled. In fact, legislation and standardization (cf. the Sarbanes-Oxley Act, the Basel II Accord, and the ISO 9000 family of standards) are forcing organizations to document their processes. These processes are often not enforced by information systems. However, torrents of event data are recorded by today’s information systems. These recorded events reflect how processes are really executed. Often reality deviates from the modeled behavior. Therefore, measuring the extent process executions conform to a predefined process model is increasingly important. In this paper, we propose an approach to measure the precision of a process model with respect to an event log. Unlike earlier approaches, we first align model and log thus making our approach more robust, even in case of deviations. The approach has been implemented in the ProM 6 tool and evaluated using both artificial and real life cases.

Enhancing precision in Process Conformance: Stability, confidence and severity

Process Conformance is becoming a crucial area due to the changing nature of processes within an Information System. By confronting specifications against system executions (the main problem tackled in process conformance), both system bugs and obsolete/incorrect specifications can be revealed. This paper presents novel techniques to enrich the process conformance analysis for the precision dimension. The new features of the metric proposed in this paper provides a complete view of the precision between a log and a model. The techniques have been implemented as a plug-in in an open-source Process Mining platform and experimental results witnessing both the theory and the goals of this work are presented.

Process mining from a basis of state regions

A central problem in the area of Process Mining is to obtain a formal model that represents selected behavior of a system. The theory of regions has been applied to address this problem, enabling the derivation of a Petri net whose language includes a set of traces. However, when dealing with real-life systems, the available tool support for performing such task is unsatisfactory, due to the complex algorithms that are required. In this paper, the theory of regions is revisited to devise a novel technique that explores the space of regions by combining the elements of a region basis. Due to its light space requirements, the approach can represent an important step for bridging the gap between the theory of regions and its industrial application. Experimental results improve in orders of magnitude state-of-the-art tools for the same task.

Online techniques for dealing with concept drift in process mining

Concept drift is an important concern for any data analysis scenario involving temporally ordered data. In the last decade Process mining arose as a discipline that uses the logs of information systems in order to mine, analyze and enhance the process dimension. There is very little work dealing with concept drift in process mining. In this paper we present the first online mechanism for detecting and managing concept drift, which is based on abstract interpretation and sequential sampling, together with recent learning techniques on data streams.

Genet: A Tool for the Synthesis and Mining of Petri Nets

State-based representations of concurrent systems suffer from the well known state explosion problem. In contrast, Petri nets are good models for this type of systems both in terms of complexity of the analysis and in visualization of the model. In this paper we present Genet, a tool that allows the derivation of a general Petri net from a state-based representation of a system. The tool supports two modes of operation: synthesis and mining. Applications of these two modes range from synthesis of digital systems to Business Intelligence.