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

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conference contribution
posted on 2024-11-14, 09:14 authored by Qiang He, Xiaodong Zhu, Dongwei Li, Shuliang Wang, Jun ShenJun Shen, Yun Yang
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.

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Citation

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.

Parent title

IEEE International Conference on Cloud Computing, CLOUD

Volume

2017-June

Pagination

74-81

Language

English

RIS ID

113206

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