DocumentCode :
536019
Title :
A new KDD method based on hypergraph clustering model for farmland evaluation
Author :
Liu, Yang ; Zhang, Shiyi
Author_Institution :
Sch. of Resource & Environ. Sci., Wuhan Univ., Wuhan, China
Volume :
2
fYear :
2010
fDate :
9-10 Oct. 2010
Firstpage :
364
Lastpage :
367
Abstract :
There are some shortages in usual methods for land evaluation that too many manual interferences into the calculating procession. A hypergraph clustering model is designed with the knowledge discovery method in this paper based on fuzzy frequent itemsets to conduct the evaluation for quality of farmland. It executes the mining association rules to the fuzzy itemsets given by the definition of evaluation factors, and analyzes the clusters with the HMETIS segmentation method, finally devises the transactions similarity function to cluster the services. In the result, this method could not only determine the quality rating of each units of farmland, but also give the quality description for each grade. With the following example in Guangdong Province, China, the result is testified.
Keywords :
data mining; database management systems; fuzzy set theory; geophysics computing; graph theory; pattern clustering; HMETIS segmentation method; KDD method; association rules mining; farmland evaluation; farmland quality; fuzzy frequent itemsets; hypergraph clustering model; knowledge discovery in database; Analytical models; Cities and towns; Clustering algorithms; Educational institutions; Irrigation; Itemsets; Surface texture; data mining; farmland evaluation; fuzzy frequent itemsets; hypergraph clustering model; knowledge discovery in database;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Future Information Technology and Management Engineering (FITME), 2010 International Conference on
Conference_Location :
Changzhou
Print_ISBN :
978-1-4244-9087-5
Type :
conf
DOI :
10.1109/FITME.2010.5656290
Filename :
5656290
Link To Document :
بازگشت