Supporting Data Mining of Large Databases by Visual Feedback Queries

In this paper, we describe a query system that provides visual relevance feedback in querying large databases. Our goal is to support the process of data mining by representing as many data items as possible on the display. By arranging and coloring the data items as pixels according to their relevance for the query, the user gets a visual impression of the resulting data set. Using an interactive query interface, the user may change the query dynamically and receives immediate feedback by the visual representation of the resulting data set. Furthermore, by using multiple windows for different parts of a complex query, the user gets visual feedback for each part of the query and, therefore, may easier understand the overall result. Our system allows to represent the largest amount of data that can be visualized on current display technology, provides valuable feedback in querying the database, and allows the user to find results which, otherwise, would remain hidden in the database.

• Type: Conference
• Year: 1994
• Where: ICDE
• Authors: Daniel A. Keim, Hans-Peter Kriegel, Thomas Seidl
• Keywords: Data Items, Data Set, Database, ICDE 1994, Visual Relevance Feedback