New Association rule mining on multiband satellitic image data

Association rule mining is one of the most important problems of data mining. Since multi-band image data contains huge amounts of information, itpsilas a very potent area to discover useful rules. Compared to traditional market ldquobasket datardquo, multiband satellitic image has specific characte...

Full description

Saved in:
Bibliographic Details
Published in2008 Chinese Control and Decision Conference pp. 3322 - 3325
Main Authors Hai-hui Wang, Min Ren
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Algorithm design and analysis
Association Rule Mining
Association rules
Data mining
Itemsets
Multiband Satellitic Image Data
Partitioning algorithms
Pixel
Remote sensing
Transaction Patterns
Online AccessGet full text
ISBN9781424417339
1424417333
ISSN1948-9439
DOI10.1109/CCDC.2008.4597944

Cover

More Information
Summary:Association rule mining is one of the most important problems of data mining. Since multi-band image data contains huge amounts of information, itpsilas a very potent area to discover useful rules. Compared to traditional market ldquobasket datardquo, multiband satellitic image has specific characteristics and also presents specific difficulties. Two problems need to be solved to apply association rule mining on multiband satellitic images. The first is to deal with quantitative attributes. The second is to efficiently handle huge quantities of information. For the first problem, partitioning quantitative data into intervals is a simple but effective way. For the second problem, we propose a new approach based on transaction patterns and occurrences counting, which simplifies the calculation of support and is much more efficient. A modified apriori algorithm is given for which performance analysis shows obvious improvements.
ISBN:9781424417339
1424417333
ISSN:1948-9439
DOI:10.1109/CCDC.2008.4597944