Conference
ALID
Abstract
Detecting dominant clusters is important in many analytic applications. The state-of-the-art methods find dense subgraphs on the affinity graph as dominant clusters. However, the time and space complexities of those methods are dominated by the construction of affinity graph, which is quadratic with respect to the number of data points, and thus are impractical on large data sets. To tackle the challenge, in this paper, we apply
…
Authors
Chu L; Wang S; Liu S; Huang Q; Pei J
Volume
8
Pagination
pp. 826-837
Publisher
Association for Computing Machinery (ACM)
Publication Date
4 2015
DOI
10.14778/2757807.2757808
Conference proceedings
Proceedings of the VLDB Endowment
Issue
8
ISSN
2150-8097