High-level activity abstraction using low-level event logs generated from workstation applications | |
| Author | Datta, Indrajeet |
| Call Number | AIT RSPR no.CS-21-02 |
| Subject(s) | Data mining Business intelligence Management--Data processing Petri nets |
| Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Research studies project report ; no.CS-21-02 |
| Abstract | Event data collected by information systems as business processes execute in organizations can be used to discover or reverse engineer business process models through a technique called process mining. Process mining uses data mining algorithms applied to event log data to discover process models, identify trends and patterns, and find bottlenecks in business processes for the aims of understanding and optimization. Process mining tools rely on well-structured event logs to mine business processes. These events are usually generated by information systems (IS) during execution of the business processes. However, execution of business processes often requires the use of additional tools, which are external to the IS, such as document editors and communication tools (emails, instant messaging, etc). For instance, actors may use a document editor to write a project objectives in the project management business process. These tools, in this re search study, are referred as workstation applications or desktop applications. To be able to mine these processes, it is important to collect event logs from these workstation applica tions. Additional event-logging programs are required to collect data from the workstation applications. One such event logger is developed by Orange S.A., which collects user activ ity from workstation computers. Although the data collected by the event logger is detailed and useful, it is very low-level and does not associate event data with higher level business activity as needed for process mining. The global objective of my research study is to propose a process mining approach that takes into account the activities achieved using workstation applications in order to provide a consistent and comprehensive view of the business processes. My goal is to make a use case of the event log data collected from workstation applications by event loggers such as the one developed by Orange, to be able to be used in process mining by developing an algorithm to abstract the low-level event data it generates to obtain high-level business process activities which then can be used to discover and analyze business process models through process mining. |
| Year | 2020 |
| Corresponding Series Added Entry | Asian Institute of Technology. Research studies project report ; no.CS-21-02 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Dailey, Matthew N.; |
| Examination Committee(s) | Chutiporn Anutariya |
| Degree | Research Studies Project Report (M. Sc.) - Asian Institute of Technology, 2020 |