Distributed Partial Clustering
Distributed Partial Clustering
复制标题
分布式部分集群
DOI:
10.1145/3322808
复制
发表时间:
2019
影响因子:
1.6
通讯作者:
Zhang, Qin
中科院分区:
文献类型:
--
作者:
Guha, Sudipto;Li, Yi;Zhang, Qin
Recent years have witnessed an increasing popularity of algorithm design for distributed data, largely due to the fact that massive datasets are often collected and stored in different locations. In the distributed setting, communication typically dominates the query processing time. Thus, it becomes crucial to design communication-efficient algorithms for queries on distributed data. Simultaneously, it has been widely recognized that partial optimizations, where we are allowed to disregard a small part of the data, provide us significantly better solutions. The motivation for disregarded points often arises from noise and other phenomena that are pervasive in large data scenarios.In this article, we focus on partial clustering problems,k-center,k-median, andk-means objectives in the distributed model, and provide algorithms with communication sublinear of the input size. As a consequence, we develop the first algorithms for the partialk-median and means objectives that run in subquadratic running time. We also initiate the study of distributed algorithms for clustering uncertain data, where each data point can possibly fall into multiple locations under certain probability distribution.
DOI:
10.1006/jcss.1997.1547
发表时间:
1998
期刊:
J. Comput. Syst. Sci.
影响因子:
--
作者:
P. Duris;J. Rolim
通讯作者:
J. Rolim
DOI:
10.1016/j.tcs.2015.08.017
发表时间:
2014
期刊:
Theor. Comput. Sci.
影响因子:
--
作者:
Haitao Wang;Jingru Zhang
通讯作者:
Jingru Zhang
DOI:
10.1201/9781315373515-18
发表时间:
2018
期刊:
J. Comput. Syst. Sci.
影响因子:
--
作者:
C. Aggarwal
通讯作者:
C. Aggarwal