Dear guest, welcome to this publication database. As an anonymous user, you will probably not have edit rights. Also, the collapse status of the topic tree will not be persistent. If you like to have these and other options enabled, you might ask Pascal Held for a login account.
This site is powered by Aigaion - A PHP/Web based management system for shared and annotated bibliographies. For more information visit www.aigaion.nl. SourceForge.hetLogo
 [BibTeX] [RIS]
Visual Data Mining of Agriculture Data
Type of publication: Inproceedings
Citation: russ2009mldm
Booktitle: Machine Learning and Data Mining in Pattern Recognition, 6th International Conference (MLDM 2009)
Series: Poster Proceedings
Year: 2009
Month: July
Pages: 30--44
Publisher: IBaI publishing
Location: Leipzig, Germany
ISSN: 1864-9734
ISBN: 978-3-940501-04-2
Abstract: Precision agriculture (PA) and information technology (IT) are closely interwoven. The former usually refers to the application of nowadays' technology to agriculture. Due to the use of sensors and GPS technology, in today's agriculture many data are collected. Making use of those data via IT often leads to dramatic improvements in efficiency. For this purpose, the challenge is to change these raw data into useful information. Techniques or methods are required which use those data to their full extent -- clearly being a data mining task. This paper presents experimental results on real and recent agriculture data that aid in the first part of the data mining process: understanding and visualizing the data. Self-organizing maps and multidimensional scaling techniques will be used to reduce the high-dimensional input data to two dimensions. The processed data can then be visualized appropriately on 2D maps. An analysis of correlations and interdependencies in the data set will be given, based on the visualization.
Keywords:
Authors Ruß, Georg
Kruse, Rudolf
Schneider, Martin
Wagner, Peter
Editors Perner, Petra
Added by: [GR]
Total mark: 0
Attachments
  • russ2009mldm.pdf
Notes
    Topics