Are you looking for a Master’s thesis topic that solves a challenging real-world problem, allows you to become a specialist in the area of processes and information systems, gives you cutting-edge knowledge to solve today’s problems regarding processes and their use in all kinds of organizations and companies?
The PA group offers you thesis topics and supervision in a group that has invented and developed cutting edge technologies that were applied in over 100 different companies and is now being used in various industrial tools, that has set and contributed to various standards in the area of process-aware information systems, that actively cooperates with many large companies in the area of process-aware information systems in the Netherlands and worldwide, as well as with universities and researchers from all over the world (we are currently running 17 projects with different partners), that received a perfect score in the 2012 evaluation of Computer Science groups in the Netherlands, that gives you clear and regular guidance through the challenges of a Master’s thesis project with the freedom to develop your own ideas, and that after all is fun and supportive to work with.
Background Customer journey thinking is getting more and more established in companies. Customers are getting more volatile with higher expectations and competition is fierce. With customer journey analytics it is possible to use a personal approach on a large dataset of customer behaviour and customer experience. In the field of customer journey analytics multiple well-known Read More …
You’ve learned about process mining during your courses, but how much do you know about creating the event log for process mining? In business, creating the event log required for process mining is one of the most time-intensive, most complex parts of a process mining project. At Konekti, we’ve built a platform that simplifies and Read More …
Process models are used to describe and reason about the execution of a process (e.g., package delivery) where a process instance (package), also called as a case, moves through the system. A case in a process is often subject to interaction with other cases and/or resources (e.g. deliverer), impacting the workflow. Event logs record which Read More …
Philips Healthcare produces an image-guided therapy system, called Azurion, that helps surgeons to execute complex procedures. In the past Master projects at Philips Healthcare, Master students have already developed a visual logfile analysis tool that has been making waves within our organization and conformance checking methods to address anti-patterns describing unwanted behavior. Now, we’re looking Read More …
Description Reliable analysis of performance problems and their root causes requires data of a high quality to understand how cases were handed from one employee to another and how they were processed in queues. However, the recorded event data is often of lower quality, e.g., information about queues is missing. The objective of this project Read More …
Company Description Smart Host (https://www.smart-host.com) was founded in 2017 and is now one of the leading CRM systems for hotels in Europe. Based in Berlin, Germany we provide a SaaS solution to help hotels maximise their revenue and at the same time become better hosts by gathering valuable information about their guests and their individual Read More …
Context This project is defined in the scope of the Smart Journey Mining project [1, 9]. The SJM project vision is to increase the quality of services by uniting research on customer journeys and process mining using new developments in logic-based analysis and artificial intelligence. Research in SJM is done together with SINTEF Digital (Norway), Read More …
Responsible Process Mining as a topic is introduced in [1]: “The prospect of data misuses negatively affecting our life has led to the concept of responsible data science. It advocates for responsibility to be built, by design, into data management, data analysis, and algorithmic decision-making techniques such that it is made difficult or even impossible Read More …
This Master project is offered by the Configuration Management department of ASML and was developed together with EAISI (Eindhoven Artificial Intelligence Systems Institute, https://eaisi.tue.nl/). Background information Department: Configuration Management If the journey regarding overlapping changes (multiple changes impacting the same item within the same timeframe) has taught is one thing, it is that the analysis Read More …
Background Within companies customer journey thinking is getting more and more established. Customers are getting more volatile and competition is fierce. With customer journey analytics is it possible to use a personal approach on large dataset of customer behaviour and customer experience. In the field of customer journey analytics multiple well-known fields are combined, Read More …
CPN Tools is a tool that is well-known in the Petri net community. CPN Tools provides a mature environment for constructing, simulating, and performing analysis of CPN (Coloured Petri Net) models. CPN Tools consists of an ML-based CPN simulator (the back-end), and a CPN editor (the front-end) that has been developed in the BETA programming Read More …
(Verpleeg- en Verzorgingshuizen en Thuiszorg (VVT) in Dutch) The St. Antonius hospital in Nieuwegein is an ambitious top clinical training hospital. Every year, more than 40,000 patients are admitted, of which 6,000 patients go home through Care Mediation with home care or to a nursing or care home. This outflow is very erratic with seasonal influences. At Read More …
Smart cities approach does not only emphasize the implementations of new technologies in a city but also highlights the importance of using new technologies for enabling citizens’ engagement in urban planning processes. In that regard, ICTs play a vital role in (i) supporting citizens to report their complaints related to the public spaces (i.e. Read More …
Query languages are essential for exploring, working with data and directly answering questions from data. SQL is the prime example for answering questions on relational data. Behavioral data is recorded in the form of events with timestamps. Various techniques such as Process Mining use the data in the form of event logs to aggregate and Read More …
Mercedes-Benz are well recognized as industry leaders in luxury service and high quality products, pushing the meaning of automobile excellence to new boundaries. You can trace the timeline of Mercedes-Benz all the way back to 1885 when Karl Benz invented the first automobile – cementing Mercedes-Benz a place in history. We know what you’re thinking, Read More …
Two of the most important parts of a hospital are the Emergency room and the Operating room. HagaZiekenhuis deals with tens of thousands of patients every year. For each patient, everything is recorded in the Electronic Patient Record (Chipsoft Hix). Exploring the data recorded by both areas of the hospital opens the possibilities to understand Read More …
The biggest problem that Dutch hospitals face today is the lack of nursing staff. Therefore, hospital beds are closed to maintain safety levels for the already admitted patients. However, patients on the waiting list or those already planned for elective care experience longer waiting times. And sometimes emergency care beds have to be closed causing Read More …
In the last decennia the pressure on different types of mobility have severely increased in the Netherlands. Therefor the need for availability and reliability has increased. Siemens Mobility supplies solutions in the Netherlands that contribute to the accessibility and quality of life in this regard. With the help of different technologies, data is being unlocked Read More …
In the last decennia the pressure on different types of mobility have severely increased in the Netherlands. Therefor the need for availability and reliability has increased. Siemens Mobility supplies solutions in this regard that contribute to everyday accessibility and quality of life. With the help of different technologies, data is being unlocked through which the operation Read More …
StrProMCDD is a recently published work that detects concept drifts in event streams (see the figure below). StrProMCDD uses several model-based distance measures to detect these deviations using an adaptive window concept. In this assignment, we would like to compare the performance of this model-based approach with log-based stream clustering approaches that try to detect drifts in Read More …
Process Discovery is an unsupervised learning problem with the task of discovering a graph-based model from sequences (or graphs) of event data that describes the data best. Generative Adversarial Neural Networks (GANNs) are a type of neural networks used to learn structures in an unsupervised fashion. The objective of this project is to explore the Read More …
Process mining assumes event data to be stored in an event log, which is technically either a relational table (attributes as columns) or a stream of events (attribute value pairs). Recently, we developed a new technique to store event data in a Graph database such as Neo4j. This allows to do process mining over various Read More …
A recent visual analytics technique called the “Performance Spectrum” https://github.com/processmining-in-logistics/psm allows us to gain more fine-grained insights into performance behavior and changes over time. A TU/e Master student showed that it is possible to mine synchronization of cases from the performance spectrum data showing that the behavior of a case depends on the mechanisms and Read More …
In many application domains, a process execution is captured using natural language. Think of medical records, customer complaints, legal records… The same holds for process models: they can be captured as text for medical guidelines, user manuals, legal regulations are typical examples of such cases. Such data forms a new challenge for the process mining Read More …
The analysis of the temporal evolution of dynamic graphs like social networks is a key challenge for understanding complex processes hidden in graph structured data. Graph evolution rules capture such processes on the level of small subgraphs by describing frequently occurring structural changes within a network. Existing rule discovery methods make restrictive assumptions on the Read More …
for event log clustering, outlier detection, and pre-processing. We recently developed a technique to detect the context of events from an event log in an efficient way through sub-graph matching. This allows to identify events and parts of event logs which are similar or different to each other, allowing to cluster traces, detect outliers, and Read More …
The quality of process mining results highly depends on the quality of the input data where noise, infrequent behaviors, log incompleteness or many different variants undercut the assumptions of process discovery algorithms, and lead to low-quality results. ProM provides numerous event log pre-processing and filtering options, but they require expert knowledge to understand when which Read More …
In the context of process mining, we are often confronted with companies willing to share their data if we can sufficiently anonymize this. However, to date, there are no well-defined plugins to do such anonymizations. Therefore, we are looking for a Master student that is willing to help us with this. Part of the project Read More …
The Block Layout can be used to create a layout for a process graph. For this, it uses well-known Petri-net-based reduction rules to reduce the entire net into a single place. For nicely structured process graphs, this layout works quite well, but for more complex structured graphs, the resulting layout needs to be improved. Either Read More …
Aligning structured process models to event logs is a far from trivial task. In complex modelling languages, inclusive OR-split/join patterns play an important role and they are known to be notoriously difficult to align to event logs due to their large state-spaces. The known Petri net translations of OR-joins rely either on token coloring or Read More …
For experimenting with process discovery and Petri nets, scientists often rely on experiments with artificial models and logs. More often than not, these models are block structured as it is easy to generate such models by simply building a random process tree and translating that into a Petri net. However, Petri nets allow for more Read More …
Replaying event logs on Petri nets, either through token-replay or using alignments, is a complex task. Especially when models become larger and have more labels, the size of the models becomes a problem. In Petri net theory, many reduction rules exist for reducing Petri nets while retaining, for example, soundness of the model. Can we Read More …
