Benoît Depaire

Benoît Depaire
Hasselt University

PhD

About

108
Publications
27,090
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1,329
Citations
Additional affiliations
September 2011 - September 2016
Hasselt University
Position
  • Professor (Assistant)

Publications

Publications (108)
Chapter
One of the goals of process discovery is to construct, from a given event log, a process model which correctly represents the underlying system. As with any abstraction, one does not necessarily want to represent all possible behavior, but only the significant behavior. While various discovery algorithms support this use case of discovering the sig...
Article
Healthcare managers are confronted with various Capacity Management decisions to determine appropriate levels of resources such as equipment and staff. Given the significant impact of these decisions, they should be taken with great care. The increasing amount of process execution data – i.e. event logs – stored in Hospital Information Systems (HIS...
Chapter
Full-text available
Process mining is a research domain that enables businesses to analyse and improve their processes by extracting insights from event logs. While determining the root causes of, for example, a negative case outcome can provide valuable insights for business users, only limited research has been conducted to uncover true causal relations within the p...
Conference Paper
Full-text available
Process mining is a research domain that enables businesses to analyse and improve their processes by extracting insights from event logs. While determining the root causes of, for example, a negative case outcome can provide valuable insights for business users, only limited research has been conducted to uncover true causal relations within the p...
Chapter
Efficient resource management is a critical success factor for all businesses. Correct insights into actual resource profiles, i.e. groups of resources performing similar activity instances, is important for successful knowledge and (human) resource management. To this end, organisational mining, a subfield of Process Mining, focuses on techniques...
Preprint
Full-text available
There is an ongoing debate in computer science how algorithms should best be studied. Some scholars have argued that experimental evaluations should be conducted, others emphasize the benefits of formal analysis. We believe that this debate less of a question of either-or, because both views can be integrated into an overarching framework. It is th...
Chapter
Full-text available
Due to the rise of IoT, event data becomes increasingly fine-grained. Faced with such data, process discovery often produces incomprehensible spaghetti-models expressed at a granularity level that doesn’t match the mental model of a business user. One approach is to use event abstraction patterns to transform the event log towards a more coarse-gra...
Chapter
In healthcare, more and more process execution information is stored in Hospital Information Systems. This data, in conjunction with data-driven process simulation, can be used, e.g. to support hospital management with Capacity Management decisions. However, real-life event logs in healthcare often suffer from data quality issues, affecting the rel...
Conference Paper
Full-text available
Although conformance checking is great at detecting process deviations, it still poses challenges that hinder adoption in auditing practice. A major challenge is that in real life a large number of deviating cases is often detected of which only a small amount are true anomalies and thus of real interest to auditors. The number of deviations is oft...
Chapter
Full-text available
Modeling complex systems by means of computational models has enabled experts to understand the problem domain without the need of waiting for the real events to happen. In that regard, Fuzzy Cognitive Maps (FCMs) have become an important modeling tool in the neural computing field because of their exibility and transparency. However, obtaining an...
Chapter
Process mining is an innovative research field aimed at extracting useful information about business processes from event data. An important task herein is process discovery. The results of process discovery are mainly non-stochastic process models, which do not convey a notion of probability or uncertainty. In this paper, Bayesian inference and Ma...
Article
Full-text available
Within the process mining domain, research on comparing control-flow (CF) discovery techniques has gained importance. A crucial building block of empirical analysis of CF discovery techniques is getting the appropriate evaluation data. Currently, there is no answer to the question of how to collect such evaluation data. This paper introduces a meth...
Article
Full-text available
The focus in the field of process mining, and process discovery in particular, has thus far been on exploring and describing event data by the means of models. Since the obtained models are often directly based on a sample of event data, the question whether they also apply to the real process typically remains unanswered. As the underlying process...
Article
Full-text available
When developing optimisation algorithms, the focus often lies on obtaining an algorithm that is able to outperform other existing algorithms for some performance measure. It is not common practice to question the reasons for possible performance differences observed. These types of questions relate to evaluating the impact of the various heuristic...
Article
Knowing the availability of human resources for a business process is required, e.g., when allocating resources to work items, or when analyzing the process using a simulation model. In this respect, it should be taken into account that staff members are not permanently available and that they can be involved in multiple processes within the compan...
Article
Full-text available
In order to survive under the ever increasing pressure to operate more efficiently, transportation companies are obliged to adopt a collaborative focus. Although organisations become increasingly aware of the inevitable character of horizontal collaboration, surveys report failure rates up to 70% for starting strategic partnerships. While a growing...
Article
Batch processing refers to an organization of work in which cases are synchronized such that they can be processed as a group. Prior research has studied batch processing mainly from a deductive angle, trying to identify optimal rules for composing batches. As a consequence, we lack methodological support to investigate according to which rules hum...
Article
The field of combinatorial optimization has inspired the development of a large number of heuristic solution procedures. These methods are commonly assessed using a competitive evaluation methodology that may give an indication of which algorithm has a better performance. A next step in the experimental analysis is to uncover “why” one algorithm pe...
Chapter
Heuristic algorithms are most commonly applied in a competitive context in which the algorithm is tested on well-known benchmarks of some problem application with the objective of obtaining better performance results than the state-of-the-art. Focusing on characterising heuristic algorithm behaviour to acquire insight and knowledge of how these sol...
Chapter
During the last decade several decision mining techniques have been developed to discover the decision perspective of a process from an event log. The increasing number of decision mining techniques raises the importance of evaluating the quality of the discovered decision models and/or decision logic. Currently, the evaluations are limited because...
Conference Paper
When a company wants to use business process simulation to support decision-making, a simulation study needs to be conducted. Using a clear stepwise method can avoid overlooking key activities during the simulation study and improves the study’s credibility towards decision-makers or project sponsors. In this tutorial, a method to perform a simulat...
Article
Over the last decades, the field of process mining has emerged as a response to a growing amount of event data being recorded in the context of business processes. Concurrently with the increasing amount of literature produced in this field, a set of tools has been developed to implement the various algorithms and provide them to end users. However...
Chapter
In the domain of process discovery, there are four quality dimensions for evaluating process models of which simplicity is one. Simplicity is often measured using the size of a process model, the structuredness and the entropy. It is closely related to the process model understandability. Researchers from the domain of business process management (...
Preprint
Full-text available
Process mining offers techniques to exploit event data by providing insights and recommendations to improve business processes. The growing amount of algorithms for process discovery has raised the question of which algorithms perform best on a given event log. Current evaluation frameworks for empirically evaluating discovery techniques depend on...
Article
Full-text available
Logistics service providers become increasingly aware of the need to collaborate to face challenges such as globalization and the heightened expectations of customers. This paper focuses on horizontal cooperation between logistics service providers in road transportation and introduces two novel conceptual models. Firstly, a decision framework for...
Article
In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. The main objectives of this research are to determine which order picking planning problems are related, to explain why and how individual pla...
Article
Learning analytics (LA) has emerged as a field that offers promising new ways to prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date, availa...
Article
Background: As an emergency department (ED) is a complex adaptive system, the analysis of continuously gathered data is valuable to gain insight in the real-time patient flow. To support the analysis and management of ED operations, relevant data should be provided in an intuitive way. Aim: Within this context, this paper outlines the developmen...
Article
Evaluating the quality of discovered process models is an important task in many process mining analyses. Currently, several metrics measuring the fitness, precision and generalization of a discovered model are implemented. However, there is little empirical evidence how these metrics relate to each other, both within and across these different qua...
Article
Full-text available
One of the objectives of railway infrastructure managers is to improve the punctuality of their operations while satisfying safety requirements and coping with limited capacity. To fulfil this objective, capacity planning and monitoring have become an absolute necessity. Railway infrastructure managers possess tremendous amounts of data about the r...
Article
Resources can organise their work in batches, i.e. perform activities on multiple cases simultaneously, concurrently or intentionally defer activity execution to handle multiple cases (quasi-) sequentially. As batching behaviour influences process performance, efforts to gain insight on this matter are valuable. In this respect, this paper uses eve...
Technical Report
Full-text available
The Process Tree notation is an emerging language for mod-eling block-structured processes. A Process Tree is inherently sound and therefore proves to be the ideal input of a simulator as it can never deadlock. However, most business process simulation tools require a translation to Petri Nets. This technical paper proposes a simulation tool for Pr...
Conference Paper
Full-text available
Process mining mainly focuses on the retrieval of process models from event logs. As these discovery algorithms make assumptions, performance analyses based on these models can present a biased view. In literature, algorithm-agnostic process metrics have been introduced. Given the critical importance of resources in the light of continuous process...
Conference Paper
Fitness and precision are two widely studied criteria to determine the quality of a discovered process model. These metrics measure how well a model represents the log from which it is learned. However, often the goal of discovery is not to represent the log, but the underlying system. This paper discusses the need to explicitly distinguish between...
Conference Paper
In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. The objective of this research is to simulate and evaluate the interaction between several storage, batching, zone picking and routing policie...
Conference Paper
Resources are a critical component of a business process as they execute the activities. These resources, especially human resources, are not permanently available and tend to be involved in multiple processes. However, a company might wish to analyze or model a single process. To this end, insights need to be gathered on the availability of a reso...
Conference Paper
Full-text available
The empirical analysis of process discovery algorithms has recently gained more attention. An important step within such an analysis is the acquisition of the appropriate test event data, i.e. event logs and reference models. This requires an implemented framework that supports the random and automated generation of event data based on user specifi...
Article
Full-text available
The paper focuses on the use of process mining (PM) to support the construction of business process simulation (BPS) models. Given the useful BPS insights that are available in event logs, further research on this topic is required. To provide a solid basis for future work, this paper presents a structured overview of BPS modeling tasks and how PM...
Article
Highlights - The emergency department is a complex adaptive system. - Predicting and controlling the behaviour of a complex system is difficult. - We suggest to shift the focus on crowding to quality and safety. - We suggest a new paradigm of analysing and managing the system.
Conference Paper
Full-text available
A resource typically executes a particular activity on a series of cases. When a resource performs an activity on several cases simultaneously, (quasi-) sequentially or concurrently, this is referred to as batch processing. Given its influence on process performance, batch processing needs to be taken into account when modeling business processes f...
Conference Paper
Accurately modeling the interarrival times (IAT) is important when constructing a business process simulation model given its influence on process performance metrics such as the average flow time. To this end, the use of real data from information systems is highly relevant as it becomes more readily available. This paper considers event logs, a p...
Conference Paper
As customer markets globalize, supply chains are increasingly depending on efficient and effective logistic systems in order to distribute products in a large geographical area. Warehouses are an important part of supply chains, and therefore warehouse operations need to work in an efficient and effective way. Currently, literature mainly focusses...
Article
Currently, process mining literature is primarily focused on the discovery of comprehensible process models that best capture the underlying behavior in event logs. Consequently, the resulting models a) aggregate information, based on algorithm-specific assumptions, and b) transform information into a simplified representation. Both characteristics...
Article
Full-text available
Currently, process mining literature is primarily focused on the discovery of comprehensible process models that best capture the underlying behavior in event logs. Consequently, the resulting models a) aggregate information, based on algorithm-specific assumptions, and b) transform information into a simplified representation. Both characteristics...
Conference Paper
The construction of a business process simulation (BPS) model requires significant modeling efforts. This paper focuses on modeling the interarrival time (IAT) of entities, i.e. the time between the arrival of consecutive entities. Accurately modeling entity arrival is crucial as it influences process performance metrics such as the average waiting...
Conference Paper
Determining the quality of a discovered process model is an important but non-trivial task. In this article, we focus on evaluating the realism level of a discovered process model, i.e. to what extent does the model contain the process behavior that is present in the true underlying process and nothing more. The IR Measure is proposed which represe...
Article
Full-text available
Past research revealed issues with artificial event data used for comparative analysis of process mining algorithms. The aim of this research is to design, implement and validate a framework for producing artificial event logs which should increase discriminatory power of artificial event logs when evaluating process discovery techniques.
Conference Paper
This paper focuses on the potential of process mining to support the construction of business process simulation (BPS) models. To date, research efforts are scarce and have a rather conceptual nature. Moreover, publications fail to explicit the complex internal structure of a simulation model. The current paper outlines the general structure of a B...
Article
Testing and controlling business processes, activities, data and results is becoming increasingly important for companies. Based on the literature, business tests can be divided into three domains, i.e. performance, risk and compliance and separate domain-specific frameworks have been developed. These different domains and frameworks hint at some a...
Conference Paper
Business process simulation models are typically built using model construction inputs such as documentation, interviews and observations. Due to issues with these information sources, efforts to further improve the realism of simulation models are valuable. Within this context, the present paper focuses on the use of process execution data in simu...
Article
Vehicle Routing Problems (VRP) are an extensively studied class of combinatorial optimization problems, with a wide spectrum of real-life applications. An impressive number of heuristic procedures have been proposed for VRP problems. However, no common, agreed-upon methodology is used to compare heuristic performance on vehicle routing problems. In...
Conference Paper
Full-text available
Three characteristics define Big Data: volume, variety, and velocity [28]. An approach for storing Big Data is presented in the paper. It is called “Natural Language Addressing” [18; 19]. Its main idea is to use internal encoding of letters of a word or phrase as elements of co-ordinate vector which may be used as hyper-space address of the informa...
Conference Paper
Severe competition in global markets and the heightened expectations of customers have caused profit margins of transport companies to shrink. In order to survive under the increasing pressure to operate more efficiently, they are obliged to adopt a collaborative focus. Carriers operating at the same level of the supply chain may cooperate horizont...
Article
In modern society, more and more attention is given to the increase in public transportation or bike use. In this regard, one of the most important issues is to find and analyse the factors influencing car dependency and the attitudes of people in terms of preferred transport mode. Although the individuals’ transport behavioural modelling is a comp...
Conference Paper
Full-text available
Artificial Intelligence has always followed the idea of using computers for the task of modelling human behaviour, with the aim of assisting decision making processes. Scientists and researchers have developed knowledge representations to formalize and organize such human behaviour and knowledge management, allowing for easy translation from the re...
Article
Transport management and behaviour modelling appears in modern societies because of the importance for all social and economic processes. Using in this field advanced computer techniques like the Artificial Intelligence ones is really relevant from the scientific, economic and social point of view. In this paper we deal with Fuzzy Cognitive Maps as...
Article
Full-text available
Associative classifiers use a set of class association rules, generated from a given training set, to classify new instances. Typically, these techniques set a minimal support to make a first selection of appropriate rules and discriminate subsequently between high and low quality rules by means of a quality measure such as confidence. As a result,...
Article
In family business literature, business professionalization is often simplified into a binary characteristic, that is, the presence of a nonfamily manager. We contend that other professionalization features, which may act simultaneously, can influence firm performance. This study addresses professionalization as a multidimensional construct, as int...
Article
Although the individuals' transport behavioural modelling is a complex task, it can produce a notable social and economic impact. In this paper, Fuzzy Cognitive Maps are explored to represent the behaviour and operation of such complex systems. An automatic approach to extract mental representations from individuals and convert them into computatio...
Article
In this paper we propose an experimental setup and statistical methodology to design and evaluate heuristic algorithms. We apply our approach to various heuristics proposed in literature for the classical VRPTW. First, a multi-level regression analysis is used to determine the algorithms’ optimal parameter values and to construct decision rules sta...
Article
This article responds to the calls from the research field to find effective ways to distinguish between different categories of family firms. The authors contribute to this literature by extending and refining previous family firm typologies. To attain this objective, the authors introduce the professionalization construct as basis for distinguish...