DocumentCode :
1668087
Title :
SNN Neighbor and SNN Density-based co-location pattern discovery
Author :
Zeng-fang, Yang ; He-wen, Tang
Author_Institution :
Department of Computer Science and Engineering, Yuxi Normal University Yuxi 653100, P.R. China
fYear :
2011
Firstpage :
1
Lastpage :
5
Abstract :
Concerning co-location pattern mining research, the definition of co-location instance in classical algorithms is clique-based. Considering the drawbacks of this definition, this work proposes a novel definition: SNN Neighbor and SNN Density-based co-location instance. Then the paper illustrates the significance of this conception and a SNN Neighbor and SNN Density-based co-location pattern mining algorithm is realized. At last, a plenty of experimental results on synthetic and real data sets show this approach is correct and flexible, and can discovery more interesting patterns that clique-based methods fail to. Further more, our solution is faster and takes less memory consumption than traditional approaches.
Keywords :
Computer science; Conferences; Data mining; Electronic mail; Geographic Information Systems; Spatial databases; Telecommunications; SNN Density; SNN Neighbor; co-location instance; co-location pattern;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E -Business and E -Government (ICEE), 2011 International Conference on
Conference_Location :
Shanghai, China
Print_ISBN :
978-1-4244-8691-5
Type :
conf
DOI :
10.1109/ICEBEG.2011.5885287
Filename :
5885287
Link To Document :
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