Visual Exploration of Categorical and Mixed Data Sets
2009 (English)In: Proceeding VAKD '09 Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration: Workshop on Visual Analytics and Knowledge Discovery, New York, USA: ACM Press, 2009, 21-29 p.Conference paper (Refereed)
For categorical data there does not exist any similarity measurewhich is as straight forward and general as the numericaldistance between numerical items. Due to this it is often difficultto analyse data sets including categorical variables or a combination of categorical and numerical variables (mixeddata sets). Quantification of categorical variables enablesanalysis using commonly used visual representations andanalysis techniques for numerical data. This paper presents a tool for exploratory analysis of categorical and mixed data, which uses a quantification process introduced in [Johansson2008]. The application enables analysis of mixed data sets by providingan environment for exploratory analysis using commonvisual representations in multiple coordinated views and algorithmic analysis that facilitates detection of potentially interesting patterns within combinations of categorical and numerical variables. The effectiveness of the quantificationprocess and of the features of the application is demonstratedthrough a case scenario.
Place, publisher, year, edition, pages
New York, USA: ACM Press, 2009. 21-29 p.
Information visualization, visual exploration, quantification, categorical data, mixed data, data mining
IdentifiersURN: urn:nbn:se:liu:diva-25572DOI: 10.1145/1562849.1562852ISBN: 978-1-60558-670-0OAI: oai:DiVA.org:liu-25572DiVA: diva2:245940
ACM SIGKDD Workshop on Visual Analytics and Knowledge DiscoveryACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery, 28 June - 1 July, Paris, France