Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network

  Advanced Search  

Automated Feature Selection through Relevance Feedback

Summary: Automated Feature Selection
through Relevance Feedback
Carsten Tusk, Krzysztof Koperski, Selim Aksoy, and Giovanni Marchisio
Insightful Corporation
1700 Westlake Ave. N, Suite 500
Seattle, WA, 98109-3044
{ctusk, krisk, saksoy, giovanni}@insightful.com
Abstract-The VisiMine [2] project aims to provide
infrastructure that would enable the analysis of large databases
containing satellite images. Our work addresses two issues. One
is the extraction of information that enables reduction of the
data from multi-spectral images into a number of features.
Second is the organization and selection of the features that
would allow flexible and scalable discovery of the knowledge
from the databases of remotely sensed images. The VisiMine
architecture distinguishes between three types of feature
vectors: pixel, region and tile.
One of the challenges in information retrieval is the proper
choice of the set of features that are the best suited for a data
mining task. The VisiMine system enables extraction of a large


Source: Aksoy, Selim - Department of Computer Engineering, Bilkent University


Collections: Computer Technologies and Information Sciences