Enriching Customer Journey Prediction in KPN with Context Data

The customer journey approach is quickly becoming the game changer within KPN to become a customer-centric service provider and to improve the customer experience to an un-telco like level. Within this context, we have already connected various touch points of the customer, including calls, chats, store visits, online visits and engineer visits, and we are Read More …

Analyzing customer journey with process mining : from discovery to recommendations

Terragni, Alessandro & Hassani, Marwan (2018). Analyzing customer journey with process mining : from discovery to recommendations. In Muhammad Younas & Jules Pagna Disso (Eds.), Proceedings – 2018 IEEE 6th International Conference on Future Internet of Things and Cloud, FiCloud 2018 (pp. 224-229). Piscataway: Institute of Electrical and Electronics Engineers (IEEE). Abstract Customer journey analysis Read More …

Towards effective generation of synthetic memory references via markovian models

Cuzzocrea, Alfredo, Mumolo, Enzo, Hassani, Marwan & Grasso, Giorgio Mario (2018). Towards effective generation of synthetic memory references via markovian models. In Ling Liu, Claudio Demartini, Ji-Jiang Yang, Thomas Conte, Kamrul Hasan, Edmundo Tovar, Zhiyong Zhang, Sheikh Iqbal Ahamed, Stelvio Cimato, Toyokazu Akiyama, Sorel Reisman, William Claycomb, Motonori Nakamura, Hiroki Takakura & Chung-Horng Lung (Eds.), Read More …

A Markov-Model-based framework for supporting real-time generation of synthetic memory references effectively and efficiently

Cuzzocrea, Alfredo, Mumolo, Enzo, Hassani, Marwan & Grasso, Giorgio Mario (2018). A Markov-Model-based framework for supporting real-time generation of synthetic memory references effectively and efficiently. Proceedings – DMSVIVA 2018 (pp. 83-90). Pittsburgh: Knowledge Systems Institute Graduate School. Abstract Driven by several real-life case studies and in-lab developments, synthetic memory reference generation has a long tradition Read More …

Detecting root causes of complaints and investigating the continuation within the customer journey

In the Dutch health care system health care insurance is obligated for all residents. The government sets the basis package and insurers compete based on price and service. Customer service is therefore very important for every health insurance company; especially in the fast changing digital world. As a result customer satisfaction is the most important Read More …

Philips HUE Product Evolution Using Stream Mining of Customer Journey

Philips HUE is a connected personal lighting system. It is controlled by a range of apps and smart home devices. To acquire Philips HUE, one starts with a starter kit that consists of a few lamps and a bridge. Subsequently, consumers decide to expand their system with additional lamps or/and physical sensors. About 50 lamps Read More …

Real-Time Model Discovery of the Service Order Process Using Stream Process Mining

Kropman Installatietechniek is a Dutch company established in 1934 and has become one of the leading companies of the Dutch installation industry. With about 800 employees, 12 regional locations and an annual turnover of more than 100 million Euro, Kropman is an integral service provider with a multidisciplinary approach. Kropman is mainly active in office Read More …

PhD position on Stream Mining for Real Time Compliance Checking

In the context of the EU H2020 project BPR4GDPR (Business Process Re-engineering and functional toolkit for GDPR compliance), a PhD position is open at the Process Analytycs (PA) group in TU/e’s Department for Mathematics and Computer Science in the domain of Stream Process Mining. Position PhD-student Department(s) Department of Mathematics & Computer Science Institutes Data Read More …

2IMI00 Seminar Process Analytics

In this seminar, a group of master students will get in touch with research in the area of Information Systems, where Process Mining and Process Analysis from Event Data are the central themes. We study recent publications in the area of process mining and practical applications on real-life examples, to provide a good insight into Read More …

2IMI05 Capita selecta process analytics

People interested in the ‘process side’ of information systems can take the course ‘Capita selecta architecture of information systems’. This course will be organized in an ad-hoc manner taking into account the interests of the student. The focus will always be on a particular ‘hot topic’ in the information systems domain. The course can, in Read More …

JM0210 Real-Time Process Mining (JADS)

The Real-Time Process Mining course is an advanced master-level process mining course where the following main contents will be covered: Dimensionality reduction and efficient preprocessing of log files Stream data mining Advanced topics in process mining, like: stream process discovery, online conformance checking and concept drift detection When the focus shifts to advanced topics in Read More …

BPR4GDPR

Business Process Re-engineering for General Data Protection Regulation Description The goal of BPR4GDPR is to provide a holistic framework able to support end-to-end GDPR-compliant intra- and interorganisational ICT-enabled processes at various scales, while also being generic enough, fulfilling operational requirements covering diverse application domains. To this end, proposed solutions will have a strong semantic foundation Read More …

Marwan Hassani

Dr. Marwan Hassani is assistant professor at the PA group with a focus on Real-Time Process Mining. His research interests include stream data mining, sequential pattern mining of multiple streams, efficient anytime clustering of big data streams and exploration of evolving graph data. He uses customer journey optimizationa and privacy-aware process mining as use cases for his Read More …

Publications in 2017

Article Scientific peer reviewed Arriagada-Benítez, M., Sepúlveda, M., Munoz-Gama, J. & Buijs, J.C.A.M. (2017). Strategies to automatically derive a process model from a configurable process model based on event data. Applied Sciences, 7(10):1023. Bolt, A., de Leoni, M. & van der Aalst, W.M.P. (2017). Process variant comparison: using event logs to detect differences in behavior Read More …