By Topic

Case-based reasoning approach in geographical data mining: Experiement and application

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Yunyan Du ; State Key Lab. of Resources & Environ. Inf. Syst., Chinese Acad. of Sci., Beijing, China ; Ce Li ; Fenzhen Su ; Wei Wen
more authors

The study deems the CBR approach as a kind of problem-oriented spatial data mining method and provides case-based similarity and reasoning algorithms to extract knowledge from geographical data. First, this paper provides problem-oriented method to represent and organize geographical cases. Second, a rough set theory-based approach was employed to quantitatively retrieve these inherent spatial relationships. Third, a general model was then proposed to calculate the spatial similarity among geographic cases considering different spatial characteristics and relationships of geographical cases. The CBR method was then tested by studying a typical geographic phenomenon, Results of the studies show that CBR method has its advantages in quantitatively analyzing spatial data as well as in solving geographical problems.

Published in:

Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009  (Volume:5 )

Date of Conference:

12-17 July 2009