Puli Madhavi, M.V.Pavan Kumar, Dr. S. Gopi Krishna


The essential challenge for several big data programs is always to search data volumes and take functional understanding for other hobbies. Focused by real-world programs controlling of massive Data were revealed to get demanding yet very compelling job. We make as browse the efficient theorem that differentiates popular features of big data rising, and signifies big human sources representation, in the idea of data mining. Recommended theorem recommends that important popular features of big data are large by heterogeneous and varied data sources self-directed with distributed furthermore to decentralized control, and complicated, developing in data associations featuring believe that big data necessitate a big intelligence to improve data for finest values. We submit big human sources depiction, in the idea of data mining which data-driven structure involves demand determined choice of information sources, mining furthermore to analysis, modelling of user interest, and contemplation on security.


Big Data; Heterogeneous; Big Data Processing; Data Mining; Decentralized; Data Sources; Modelling; Security;


Y. Lindell and B. Pinkas, “Privacy Preserving Data Mining,” J. Cryptology, vol. 15, no. 3, pp. 177-206, 2002.

W. Liu and T. Wang, “Online Active Multi-Field Learning for Efficient Email Spam Filtering,” Knowledge and Information Systems, vol. 33, no. 1, pp. 117-136, Oct. 2012.

E.Y. Chang, H. Bai, and K. Zhu, “Parallel Algorithms for Mining Large-Scale Rich-Media Data,” Proc. 17th ACM Int’l Conf. Multimedia, (MM ’09,) pp. 917-918, 2009.

R. Chen, K. Sivakumar, and H. Kargupta, “Collective Mining of Bayesian Networks from Distributed Heterogeneous Data,” Knowledge and Information Systems, vol. 6, no. 2, pp. 164-187, 2004.

Y.-C. Chen, W.-C. Peng, and S.-Y. Lee, “Efficient Algorithms for Influence Maximization in Social Networks,” Knowledge and Information Systems, vol. 33, no. 3, pp. 577-601, Dec. 2012.

A. Labrinidis and H. Jagadish, “Challenges and Opportunities with Big Data,” Proc. VLDB Endowment, vol. 5, no. 12, 2032-2033, 2012.

Full Text: PDF


  • There are currently no refbacks.

Copyright © 2012 - 2021, All rights reserved.| ijitr.com

Creative Commons License
International Journal of Innovative Technology and Research is licensed under a Creative Commons Attribution 3.0 Unported License.Based on a work at IJITR , Permissions beyond the scope of this license may be available at http://creativecommons.org/licenses/by/3.0/deed.en_GB.