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Department of Informatics Interactive Visual Data Analysis Group

Relation Discovery (open)

relation-seeking image of Jurgen Bernard's tool
Source: Bernard, Jürgen. "Exploratory search in time-oriented primary data." (2015)

Introduction
Finding relations in a dataset is a prominent task for data analytics. Sometimes relations among the data are known, and at other times they are discovered using statistical measures such as the pearson correlation coefficient. In this independent study, we want to investigate how relations are discovered in several domains using visualization techniques.

Tasks
Find research papers from the field of visual analytics, machine learning and statistics that use relation-seeking. Characterise and structure these papers on a taxonomy that is provided to you. Extend this taxonomy where necessary. Write and present a report on your findings.

Organization and learning outcomes
This independent study is offered as a 3, 6, or 9 credit module. The workload would be adjusted respective to the credits. The start date is also flexible.

This independent study allows you to:

  • Gain a deeper understanding of visual analytics and relation-seeking techniques.
  • Develop skills on effectively conducting a literature search on a specific topic.

Contact
This independent study is supervised by Madhav Sachdeva andProf. Jürgen Bernard. Please contact for any questions and the procedure for enrolling into this module.