Cost-effective Big Data Mining in the Cloud: A Case Study with K-means

Authors

Qiang He, Swinburne University of TechnologyFollow
Xiaodong Zhu, University of Shanghai for Science and Technology
Dongwei Li, University of Shanghai for Science and Technology
Shuliang Wang, University of Shanghai for Science and Technology
Jun Shen, University of WollongongFollow
Yun Yang, Swinburne University of TechnologyFollow

RIS ID

113206

Publication Details

He, Q., Zhu, X., Li, D., Wang, S., Shen, J. & Yang, Y. (2017). Cost-effective Big Data Mining in the Cloud: A Case Study with K-means. IEEE 10th International Conference on Cloud Computing 2017 (pp. 74-81). United States: IEEE.

Abstract

Mining big data often requires tremendous computationalresources. This has become a major obstacle to broad applicationsof big data analytics. Cloud computing allows data scientists to access computationalresources on-demand for building their big data analytics solutions in the cloud.