CoDA: Interactive Cluster Based Concept Discovery

نویسندگان

Stephan Günnemann

Ines Färber

Hardy Kremer

Thomas Seidl

چکیده

Large data resources are ubiquitous in science and business. For these domains, an intuitive view on the data is essential to fully exploit the hidden knowledge. Often, these data can be semantically structured by concepts. Since the determination of concepts requires a thorough analysis of the data, data mining methods have to be applied. In the field of subspace clustering, some techniques have recently shown to be effective for this task. Although these methods generate concept-based patterns, the user has to provide domain knowledge to gain reasonable concepts out of the data. Our demonstration CoDA (Concept Determination and Analysis) is a tool that supports the user in the final step of concept definition. More concretely, the user is guided through an iterative, interactive process in which concepts are suggested, analyzed, and potentially refined. The core aspect of CoDA is an intuitive, concept-driven presentation of subspace clusters such that concepts can be visually captured.

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