Study level

PhD

Master of Philosophy

Honours

Vacation research experience scheme

Faculty/Lead unit

Science and Engineering Faculty

School of Information Systems

Topic status

We're looking for students to study this topic.

Supervisors

Dr Chun Ouyang
Position
Senior Lecturer
Division / Faculty
Science and Engineering Faculty

Overview

Enterprise systems are modern information systems in today’s organisations. They record large amounts of event log data, capturing the execution of day-to-day business processes within and across organisations.

Mining event log data to drive process analytics and knowledge discovery is known as process mining. To date, various process mining techniques have been developed to help extract insights about the actual business processes with the ultimate goal of improving process performance as well as the organisations' business performance.

As an important sub-field of process mining, organisational mining focuses on discovering organisational knowledge, including organisational structures and human resources, and continuously evolving organisational dynamics.

In any organisation where humans play a dominant role, organisational mining helps managers gain a better understanding of the de facto grouping of human resources and their interactions thus to improve the related business processes as well as the organisational performance towards the building of a healthy and sustainable workforce.

While the focus of process mining is being extended from the processes’ control-flow perspective to other aspects, the research problems related to organisational mining has so far received only limited attention.

Research activities

The research activities below can be scoped to cater for your particular research project:

  • Literature review on novel approaches and techniques related to organisational mining.
  • Designing new algorithms and techniques for organisational mining based on study and application of various data mining techniques.
  • Designing new algorithms and techniques for organisational mining based on study and application of existing social network analysis techniques.
  • Designing a systematic approach for actionable process improvement informed by the findings from organisational mining.
  • Implementing new algorithms, techniques and approaches, visualisation of the results and finding, and evaluation using real event logs.

Outcomes

Upon conclusion of this research, we expect to have:

  • new/improved methods and algorithms for organisational model mining built upon suitable data mining techniques
  • novel approaches and models for discovering, reasoning and analysing intra- and inter-organisational networks by leveraging existing social network analysis capabilities
  • new tools and visualisation of the discovered organisational networks
  • knowledge discovery from process event logs for organisational improvement informed by management science.

Skills and experience

To be considered for this project, you should have:

  • familiarity with data mining, preferably process mining and/or social network analysis
  • problem-solving and critical thinking capabilities
  • programming skills such as Python and Java
  • reasonable writing skills.

Scholarships

You may be able to apply for a research scholarship in our annual scholarship round.

Annual scholarship round

Keywords

Contact

Contact the supervisor for more information.