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A Framework for Exploring Algorithms for Big Data Mining
Objectives: To proposed and implement a framework that facilitates exploration of algorithms for big data mining. Methods/Analysis: To achieve objectives, a framework is built in order to realize algorithms for big data mining and even provide Mining as a Service in cloud. As the existing data mining techniques can not work for MapReduce programming in distributed environment, we proposed new and equivalent method for k-Anonymity that can leverage the parallel processing power. Single host Hadoop is used to demonstrate the proof of concept of the proposed framework. Findings: The framework has ability to mind big data. It has the centralized service that can be used to mine data of different users. However, as of now, the framework is realized with only one algorithm that is MapReduce version of k-Anonymity which is meant for privacy preserving data mining. The application is proved to be scalable in distributed environment. The framework has provision for supporting cloud users to outsource their data for mining big data with different algorithms of their choice. The results revealed that the proposed framework can provide mining services to cloud users and help them to save money by reusing the service instead of reinventing the wheel. Novelty/Improvement: In the proposed work a mining service for cloud is proposed which is a novel idea that has not been implemented so far. It can save money and time to enterprises in the real world.
Algorithms, Big Data, Big Data Mining, Mining Service.
- Stefania R. Data mining in Cloud Computing. Database Systems Journal. 2012 Apr; 3(3):1–5.
- Bhadauria R, Borgohain R, Biswas A, Sanyal S. Secure authentication of Cloud Data Mining. API Cloud. 2013 Aug; 1–7.
- Mohammad Sharifi A, Amirgholipour SK, Alirezanejad M, Aski BS. Availability challenge of cloud system under DDOS Attack. Indian Journal of Science and Technology. 2012 Jun; 5(6):1–3.
- Dev H, Sen T, Basak M, Ali ME. An approach to protect the privacy of Cloud Data from data mining based attacks. Department of Computer Science; 2012 Nov. p. 1106–15.
- Jothi Neela T, Saravanan N. Privacy preserving approaches in Cloud: a survey. Indian Journal of Science and Technology. 2013 May; 6(5):1–5.
- Bhagyashree B. Data Mining in Cloud Computing. Department of Computer Science; 2012 Apr. p. 1–4.
- Ankita N. Using Cloud Computing to provide Data Mining Services. Department of Computer Science; 2013 Mar; 2(3):545–50.
- Anjani Sravanthi K. Web mining using Cloud Computing. 2013 April; 3(4):1–6.
- Srinivas A. A study on Cloud Computing Data Mining. International Journal of Innovative Research in Computer and Communication Engineering. 2013 Jul; 1(5):1–6.
- Neaga I. A holistic analysis of cloud based big data mining. Department of Computer Science; 2014; 2(2):56–64.
- Anathanarayanan P. Analysing big data to build knowledge based system for early detection of ovarian cancer. Indian Journal of Science and Technology. 2015 Jul; 8(14):1–7.
- Yousif J. Cloud computing and accident handling systems. International Journal of Computer Applications. 2013 Feb; 63(19):21–6.
- Ding J. Classification rules mining model with genetic algorithm in cloud computing. International Journal of Innovative Research in Computer and Communication Engineering. 2012 Jun; 48(8):24–32.
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