Data visualization for supporting query-based data mining

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The paper proposes a methodology for supporting the process of query based data mining by using visualization techniques. The query based data mining is one of the most important tasks of Knowledge Discovery in Databases (KDD). In the process of query based data mining, users hypothesize about patterns in a database and make a query to confirm the hypothesis. The proposed method supports two aspects of the process, i.e., proposing an initial hypothesis as a query and modifying the hypothesis based on the query result. In this method, an instance in a database which has several attributes with numerical or nominal values is visualized as a color bar with several color parts which correspond to attribute values. Values of a function which evaluates the utility of a hypothesis are also visualized by using colors. This visualization technique helps users find an initial hypothesis and modify the hypothesis in order to increase the usefulness of it interactively. Experimental results show that the proposed method really helps a user find interesting rules in real world databases.

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