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Research

Research Theme

Intelligent Process-Centric Information Systems

A process-centric view of information systems would describe many of the activities involving humans, organisations and applications as a collection of structured tasks performed to achieve a goal (e.g., processing a complaint). A key notion in process-centric views is to understand how a goal is achieved and how it can be done efficiently. Such a view can be applied in a wide spectrum of activity contexts, from strict organisational context (e.g., an insurance claim process) to highly flexible personal context (e.g., cooking chicken curry).

A dedicated research area called Business Process Management has successfully produced methods and techniques to design, enact, control and analyse tightly framed and well-structured operational processes. However, there are still many open issues in supporting of processes that are ad-hoc, flexible, exploratory or collaborative. These types of processes form the majority of the processes that we experience everyday.

In this research, we are primarily interested in extending the existing concepts and solutions in BPM into non-conventional, emerging application areas by taking the view that that processes are ubiquitous and intrinsically linked to data and artefacts that interact with them.

An intelligent process-oriented system proposes a various machine-facilitated understanding of the processes as well as the data/artefacts (e.g., using semantic techniques, data mining, information extraction/retrieval, text analysis, recommender techniques), leading to solutions that are highly personalised, flexible and relevant to the types of processes that mentioned earlier.

Examples of current work include applying process-centric design and development methods to engineer improved information extraction workflows; supporting complex work patterns in crowd-sourcing platforms; using social network concepts to extract informal process structures; a language to analyse informal process structure.

Research Topics

  • Semantic techniques in process-centric systems
  • Information extraction in process-centric contexts
  • Searching and querying in process-centric systems
  • Languages and models for managing flexible processes
  • Social software systems in process-centric contexts
  • Process discovery: mining from process data and artefacts

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