Visualization and Visual Analytic Techniques for Patterns

  • Wolfgang JentnerEmail author
  • Daniel A. Keim
Part of the Studies in Big Data book series (SBD, volume 51)


This chapter surveys visualization techniques for frequent itemsets, association rules, and sequential patterns. The human is crucial in the process of identifying interesting patterns and thus, mining such patterns and visualizing them is important for the decision making. The complementary feedback loop that a user may use to refine parameters through inspecting the current mining results is broadly described as visual analytics. This survey identifies visual designs for patterns of each category and analyzes and compares their strengths and weaknesses systematically. The comparison and overview help decision-makers selecting the appropriate technique for their tasks and systems while knowing about their limitations.


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Authors and Affiliations

  1. 1.Universität KonstanzKonstanzGermany

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