Abstract
Original language | English |
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Pages (from-to) | 68-79 |
Number of pages | 12 |
Journal | Egyptian Computer Science Journal |
Volume | 42 |
Issue number | 2 |
Publication status | Published - May 2018 |
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Spatial Clustering in Large Databases Using Packed X-tree. / Samson, Grace; Lou, Zhongyu.
In: Egyptian Computer Science Journal, Vol. 42, No. 2, 05.2018, p. 68-79.Research output: Contribution to journal › Article
TY - JOUR
T1 - Spatial Clustering in Large Databases Using Packed X-tree
AU - Samson, Grace
AU - Lou, Zhongyu
PY - 2018/5
Y1 - 2018/5
N2 - In this paper, we are proposing a new algorithm that improves the performance of the DBSCAN clustering algorithm using a packed X-tree. The proposed algorithm does not require the minpoints and eps values. We have extensively described how the system is achieved and we have also proposed a new effective method for finding the k-nearest neighbours of spatial objects in a large database. The study shows that the proposed method is very efficient and will greatly accelerate the operations of density based clustering in large dataset as against the existing methods.
AB - In this paper, we are proposing a new algorithm that improves the performance of the DBSCAN clustering algorithm using a packed X-tree. The proposed algorithm does not require the minpoints and eps values. We have extensively described how the system is achieved and we have also proposed a new effective method for finding the k-nearest neighbours of spatial objects in a large database. The study shows that the proposed method is very efficient and will greatly accelerate the operations of density based clustering in large dataset as against the existing methods.
M3 - Article
VL - 42
SP - 68
EP - 79
JO - Egyptian Computer Science Journal
JF - Egyptian Computer Science Journal
SN - 1110-2586
IS - 2
ER -