Inventing Discovery Tools: Combining Information Visualization with Data Mining (2001)

dc.contributor.authorShneiderman, Benen_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T10:16:15Z
dc.date.available2007-05-23T10:16:15Z
dc.date.issued2005en_US
dc.description.abstractThe growing use of information visualization tools and data mining algorithms stems from two separate lines of research. Information visualization researchers believe in the importance of giving users an overview and insight into the data distributions, while data mining researchers believe that statistical algorithms and machine learning can be relied on to find the interesting patterns. This paper discusses two issues that influence design of discovery tools: statistical algorithms vs. visual data presentation, and hypothesis testing vs. exploratory data analysis. I claim that a combined approach could lead to novel discovery tools that preserve user control, enable more effective exploration, and promote responsibility.en_US
dc.format.extent596953 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/6484
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 2005-20en_US
dc.titleInventing Discovery Tools: Combining Information Visualization with Data Mining (2001)en_US
dc.typeTechnical Reporten_US

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