DocumentCode :
441806
Title :
Qualitative spatial relationships cleaning for spatial data mining
Author :
Sun, Hai-Bin ; Li, Wen-Hui
Author_Institution :
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
Volume :
3
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
1851
Abstract :
In this article, we investigate the problem of preparing qualitative spatial relations before implementing spatial data mining by checking consistency in a constraint network, which includes topological and cardinal directional relations between pairs of spatial objects. We aim to explore potential spatial relations and possible inconsistency among the data of relationships for enforcing the correctness of spatial data mining. This task is carried out through qualitative spatial reasoning method, specifically consistency checking. We try to lay the theoretical foundation for this kind of problem. Instead of using conventional composition tables, we investigate the interactions between topological and cardinal directional relations with the aid of rules. These rules are shown to be sound, i.e. the deductions are logically correct. Based on these rules, an improved constraint propagation algorithm is introduced to enforce the path consistency. An example is presented to show the utility of these rules.
Keywords :
computational complexity; constraint handling; data integrity; data mining; relational databases; spatial data structures; spatial reasoning; visual databases; cardinal directional relations; computational complexity; consistency checking; constraint network; constraint propagation; path consistency; qualitative spatial relationship cleaning; spatial data mining; spatial objects; spatial relations; topological directional relations; Cleaning; Computational complexity; Computer networks; Computer science education; Data mining; Knowledge engineering; Laboratories; Spatial databases; Sun; Topology; Qualitative spatial reasoning; computational complexity; consistency checking; spatial data mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527247
Filename :
1527247
Link To Document :
بازگشت