Transplantation of Data Mining Algorithms to Cloud Computing Platform when Dealing Big Data

TL;DR

This paper reviews the challenges of applying traditional data mining algorithms to cloud computing platforms for big data, emphasizing that current Map-Reduce based platforms are insufficient for all data mining needs and highlighting the importance of adapting algorithms for real-time cloud environments.

Contribution

It discusses the limitations of existing cloud platforms for big data mining and emphasizes the need to transplant and adapt data mining algorithms for real-time cloud computing.

Findings

Map-Reduce platforms cannot solve all big data problems

Transplanting data mining algorithms is a key research focus

Real-time cloud data mining requires algorithm adaptation

Abstract

This paper made a short review of Cloud Computing and Big Data, and discussed the portability of general data mining algorithms to Cloud Computing platform. It revealed the Cloud Computing platform based on Map-Reduce cannot solve all the Big Data and data mining problems. Transplanting the general data mining algorithms to the real-time Cloud Computing platform will be one of the research focuses in Cloud Computing and Big Data.