Ludwig-Maximilians-Universität München, Institut für Informatik
Technical Report 93-10
- TITLE:
-
Supporting Data Mining of Large Databases by Visual Feedback Queries
- DATE:
-
November 1993
- AUTHORS:
- Daniel A. Keim
- Hans-Peter Kriegel
- Thomas Seidl
- {keim, kriegel, seidl}@informatik.uni-muenchen.de
- Institut für Informatik
- Universität München
- Leopoldstr. 11B
- D-80802 München (Germany)
- KEYWORDS:
-
Data Mining, Visual Query Systems, Visual Relevance Feedback,
Interfaces to Database Systems, Visualizing Large Data Sets,
Visualizing Multidimensional and Multivariate Data, Interface and
Visualization Technology
- ABSTRACT:
-
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.
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