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