2021
DOI: 10.1145/3474842
|View full text |Cite
|
Sign up to set email alerts
|

Significant DBSCAN+: Statistically Robust Density-based Clustering

Abstract: Cluster detection is important and widely used in a variety of applications, including public health, public safety, transportation, and so on. Given a collection of data points, we aim to detect density-connected spatial clusters with varying geometric shapes and densities, under the constraint that the clusters are statistically significant. The problem is challenging, because many societal applications and domain science studies have low tolerance for spurious results, and clusters may have arbitrary shapes… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4
1

Relationship

0
5

Authors

Journals

citations
Cited by 8 publications
references
References 33 publications
0
0
0
Order By: Relevance