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PAMI
2010
164views more  PAMI 2010»
13 years 6 months ago
Large-Scale Discovery of Spatially Related Images
— We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of p...
Ondrej Chum, Jiri Matas
DBVIS
1993
101views Database» more  DBVIS 1993»
13 years 11 months ago
Using Visualization to Support Data Mining of Large Existing Databases
In this paper, we present ideas how visualization technology can be used to improve the difficult process of querying very large databases. With our VisDB system, we try to provid...
Daniel A. Keim, Hans-Peter Kriegel
IDEAS
1999
IEEE
123views Database» more  IDEAS 1999»
13 years 12 months ago
Improving OLAP Performance by Multidimensional Hierarchical Clustering
Data-warehousing applications cope with enormous data sets in the range of Gigabytes and Terabytes. Queries usually either select a very small set of this data or perform aggregat...
Volker Markl, Frank Ramsak, Rudolf Bayer
VISSYM
2003
13 years 9 months ago
Adaptive Smooth Scattered Data Approximation for Large-scale Terrain Visualization
We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement an...
Martin Bertram, Xavier Tricoche, Hans Hagen
ICDM
2003
IEEE
138views Data Mining» more  ICDM 2003»
14 years 28 days ago
Ontologies Improve Text Document Clustering
Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large sets of documents into a small number of meaningful ...
Andreas Hotho, Steffen Staab, Gerd Stumme