Theoretically-Efficient and Practical Parallel DBSCAN
© 2020 Association for Computing Machinery. The DBSCAN method for spatial clustering has received significant attention due to its applicability in a variety of data analysis tasks. There are fast sequential algorithms for DBSCAN in Euclidean space that take O(nłog n) work for two dimensions, sub-qu...
Main Authors: | Wang, Yiqiu, Gu, Yan, Shun, Julian |
---|---|
Format: | Article |
Language: | English |
Published: |
ACM
2021
|
Online Access: | https://hdl.handle.net/1721.1/136631 |
Similar Items
-
Theoretically-Efficient and Practical Parallel DBSCAN
by: Wang, Yiqiu, et al.
Published: (2022) -
Theoretically and practically efficient parallel nucleus decomposition
by: Shi, Jessica, et al.
Published: (2022) -
Theoretically and Practically Efficient Parallel Nucleus Decomposition (Abstract)
by: Shi, Jessica, et al.
Published: (2023) -
Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering
by: Wang, Yiqiu, et al.
Published: (2022) -
Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering
by: Wang, Yiqiu, et al.
Published: (2022)