Cloud-based big data mining & analyzing services platform integrating R

Proceedings - 2013 International Conference on Advanced Cloud and Big Data, CBD 2013

Volumn , Issue , 2013, Pages 147-151

  Ye, Feng ^a,b   Wang, Zhi Jian ^a,b   Zhou, Fa Chao ^b   Wang, Ya Pu ^b   Zhou, Yuan Chao ^b  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^b HOHAI UNIVERSITY   (China)

Author keywords

big data; cloud computing; data mining and analyzing; K Mean clustering; RHadoop

Indexed keywords

CLOUD COMPUTING; DATA MINING; ELECTRONIC COMMERCE;

ANALYTIC FUNCTIONS; K-MEAN CLUSTERING; K-MEANS ALGORITHM; PROCESSING LAYER; RHADOOP; SERVICES PLATFORMS; TRAFFIC MANAGEMENT; VIRTUALIZATION LAYERS;

BIG DATA;

EID: 84903590331     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CBD.2013.13     Document Type: Conference Paper

References (20)

1. IBM. What is big data: Bring big data to the enterprise, 2012, http://www-01.ibm.com/software/data/bigdata/
2. N. Marz and J. Warren. Big Data: Principles and best practices of scalable realtime data systems (MEAP Edition). Manning Publications, 2012, pp. 1-25.
3. C. Ji, Y. Li, W. Qiu, et al. Big Data Processing in Cloud Computing Environment. San Marcos, 12th International Symposium on Pervasive Systems, Algorithms and Networks (ISPAN), 2012, pp. 17-23.
4. F. Zulkernine, M. Bauer, A. Aboulnaga. Towards Cloud-based Analytics-as-a-Service (CLAaaS) for Big Data Analytics in the Cloud. Santa Clara, 2013 IEEE International Congress on Big Data, 2013, pp. 62-69.
5. G. Zhang, C. Li, Y. Zhang, et al. DataCloud: An Efficient Massive Data Mining and Analysis Framework on Large Clusters. Haikou, 2012 Ninth Web Information Systems and Applications Conference (WISA), 2012, pp. 198-203.
6. D. Talia. Clouds for Scalable Big Data Analytics. Computer, Vol.46 No.5, 2013, pp. 98-101.
7. L. Zhao, S. Sakr, A. Liu. On the Spectrum of Web Scale Data Management [A]. L. Wang, R. Ranjan, J. Chen, et al. Cloud Computing: Methodology, Systems and Applications [M]. Boca Raton: CRC Press, 2012, pp. 488-506.
8. S. Das, Y. Sismanis, K.S. Beyer, et al. Ricardo: Integrating R and Hadoop. New York, Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, 2010, pp. 987-998.
9. T. Hey, S. Tansley, K. Tolle. The Fourth Paradigm: Data-Intensive Scientific Discovery. Washington: Microsoft Research, 2009, pp. xii-xiii.
10. RHadoop. https://github.com/RevolutionAnalytics/RHadoop/wiki
11. B. Furht and A. Escalante. Handbook of Cloud Computing [M]. New York: Springer, 2010, pp. 1-20.
12. A. Kalapatapu and M. Sarkar. Cloud Computing: An Overview [A]. L. Wang, R. Ranjan, J. Chen, et al. Cloud Computing: Methodology, Systems and Applications [M]. Boca Raton: CRC Press, 2012, pp. 6-24.
13. Apache Cloudstack. http://cloudstack.apache.org/
14. J. Lin, C. Dyer. Data-Intensive Text Processing with MapReduce. Morgan & Claypool Publishers, 2010, pp. 1-64.
15. J. Dean and S. Ghemawat, "Mapreduce: simplified data processing on large clusters," Communications of the ACM, vol. 51 no. 1, 2008, pp. 107-113.
16. Hadoop. http://hadoop.apache.org/
17. T. White. Hadoop: The Definitive Guide (Third Edition). Sebastopol: O'Reilly, 2012, pp. 1-16.
18. J. Maindonald and W.J. Braun. Data Analysis and Graphics Using R (Third Edition). New York: Cambridge University Press, 2010, pp. 1-41.
19. J. Adler. R in a Nutshell (Second Edition). Sebastopol: O'Reilly, 2012, pp. 213-500.
20. Kyuseok Shim. MapReduce Algorithms for Big Data Analysis. Proceedings of the VLDB Endowment, 2012, pp. 2016-2017.