Alignments In Process Mining and Social Sequence Analysis

Overview

In process mining, we perform computational analyses of sequential data in order to help organisations improve, in settings from ride-sharing platforms to government departments. In social sequence analysis, we perform computational analysis on sequential data to understand small or large structures in society, such as the progress of careers of 18^th century German musicians, or the progress of nations through different stages of economic development.

In both process mining and social sequence analysis, calculation of "alignments" for is a key technique for precise comparison of different parts of the data set. This project will conduct a detailed technical survey of these alignment techniques, and investigate ways they may be consolidated, classified, and formally generalised. This will include quantitative and experimental evaluations of techniques on real-life datasets from both process mining and social sequence analysis.

Research activities

• Review alignment research in the social sequence analysis and process mining literature.
• Build, reuse and extend data and process science tools including in Python, Java, R.
• Work closely with researchers in the Process Science group in Information Systems.

Outcomes

• Quantitative measurement and experimental evaluation of different techniques and algorithms.
• Tools supporting the above.
• Research-level report or paper sharing the analysis and results.

Skills and experience

• Programming or data science scripting skills

Keywords

• process mining
• alignments
• social sequence analysis

Contact

Contact the supervisor for more information.