Ludwig-Maximilians-Universität München, Institut für Informatik
Technical Report 93-09
- TITLE:
-
Visual Feedback in Querying Large Databases
- DATE:
-
October 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:
-
Visual Query Systems, Visual Relevance Feedback, Interfaces to Database Systems, Visualizing Large Data Sets, Visualizing Multi-dimensional and Multivariate Data
- ABSTRACT:
-
In this paper, we describe a database query system that provides visual
relevance feedback in querying large databases. The goal of our system is to
support the query specification process by using each pixel of the display to
represent one data item of the database. By arranging and coloring the pixels
according to the relevance for the query, the user gets a visual impression of
the resulting data set. Using sliders for each condition of the query, the
user may change the query dynamically and receives immediate feedback by the
visual representation of the resulting data set. 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.
The system may be used to query any database that contains tens of thousands
to millions of data items, but it is especially helpful to explore large data
sets with an unknown distribution of values and to find the interesting hot
spots in huge amounts of data. The direct feedback allows to visually display
the influence of incremental query refinements and, therefore, allows a
better, easier and faster query specification.
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