A Study On Implementation of Cloud Computing Technology using Data Mining Algorithms

Author(s):  
Aljwhrh Almtrf ◽  
Mohamed Zohdy
2018 ◽  
Vol 48 (4) ◽  
pp. 281-285
Author(s):  
Y. J. HAO

The data mining algorithm based on cloud computing is studied and analyzed in this paper. Firstly, the research status and background of the data mining algorithms based on cloud computing are introduced briefly. Secondly, the design of Hash algorithm under cellular neural network is introduced which is needed in this paper. Next, the design of wavelet data compression algorithm for wireless sensor networks is described. Finally, the experimental results and the optimization similarity analysis are obtained. The analysis results show that the data mining algorithm based on cloud computing constructed in this paper plays an important role in data mining, and can improve the data mining algorithm of cloud computing and the development level of cloud computing technology and big data technology to some extent.


Author(s):  
Ari Fadli ◽  
Azis Wisnu Widhi Nugraha ◽  
Muhammad Syaiful Aliim ◽  
Acep Taryana ◽  
Yogiek Indra Kurniawan ◽  
...  

Author(s):  
Efat Jabarpour ◽  
Amin Abedini ◽  
Abbasali Keshtkar

Introduction: Osteoporosis is a disease that reduces bone density and loses the quality of bone microstructure leading to an increased risk of fractures. It is one of the major causes of inability and death in elderly people. The current study aims at determining the factors influencing the incidence of osteoporosis and providing a predictive model for the disease diagnosis to increase the diagnostic speed and reduce diagnostic costs. Methods: An Individual's data including personal information, lifestyle, and disease information were reviewed. A new model has been presented based on the Cross-Industry Standard Process CRISP methodology. Besides, Support Vector Machine (SVM) and Bayes methods (Tree Augmented Naïve Bayes (TAN)) and Clementine12 have been used as data mining tools. Results: Some features have been detected to affect this disease. The rules have been extracted that can be used as a pattern for the prediction of the patients' status. Classification precision was calculated to be 88.39% for SVM, and 91.29% for  (TAN) when the precision of  TAN  is higher comparing to other methods. Conclusion: The most effective factors concerning osteoporosis are detected and can be used for a new sample with defined characteristics to predict the possibility of osteoporosis in a person.  


2014 ◽  
Vol 926-930 ◽  
pp. 2280-2283
Author(s):  
Qiong Ren

With the increasing of input data size, process cost will be very long, for the explosive growth of the Internet data even reached the point of single machine can handle. This article mainly introduces the architecture of the concept of cloud computing and, the mainstream of the analysis of the current data mining algorithms, based on cloud computing to develop the data mining system, providing the operation feasibility of data mining in cloud computing platform, having strong guiding significance.


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