A Novel Algorithm for Big Data Clustering

Authors

  • Gujare VK Departmen of Computer Science & Engineering, RGPV Bhopal India
  • Malviya P Departmen of Computer Science & Engineering, RGPV Bhopal India

Keywords:

Big data, Clustering

Abstract

Now a day, large amounts of heterogeneous digital data is available this big data need to be carefully examined for analysis point of view. Big data is nothing but a large volume of heterogeneous and distributed data collection. In real world big data applications has contain huge amount of continuously grow able data but it is very costly to clean up, extract , manage and process data using present software tools. Fast and accurate retrieval of the relevant information from dataset has always been a significant issue. Prominent and accurate data clustering is a main task of exploratory data analysis and data mining applications. Clustering process is one of the data mining techniques for dividing informative dataset into group and it is a kind of unsupervised data mining technique.

References

BABU, G.P. and MARTY, M.N. 1994. Clustering with evolution strategies Pattern Recognition, 27, 2, 321-329.

McKinsey Global Institute (2011) Big Data: The next frontier for innovation, competition and productivity.

Shiv Pratap Singh Kushwah, Keshav Rawat, Pradeep Gupta” Analysis and Comparison of Efficient Techniques of Clustering Algorithms in Data Mining” International Journal of Innovative

Chen, H., Chaing, R.H.L. and Storey, V.C. (2012) Business Intelligence and Analytics: From Big Data to Big Impact, MIS Quarterly, 36, 4, pp. 1165-1188.

Neelamadhab Padhy, Dr. Pragnyaban Mishra and Rasmita Panigrahi, “The Survey of Data Mining Applications And Feature Scope”, International Journal of Computer Science and Informatio Processing(CSIP).

Wu Yuntian, Shaanxi University of Science and Technology, “Based on Machine Learning of Data Mining to Further Explore”, 2012 International Conference on Machine Learning Banff, Canada.

Guo, G, Neagu, D. (2005) Similarity-based Classifier Combination for Decision Making . Proc. Of IEEE International Conference on Systems, Man and Cybernetics, pp. 176-181

Varun Kumar and Nisha Rathee, ITM University, “Knowledge discovery from database Using an integration of clustering and classification”, International Journal of Advanced Computer Science and Applications, Vol. 2, No.3, March 2011.

Wu, X., Zhu, X., Wu, G., Ding, W. (2014) Data Mining with Big Data, Knowledge and Data Enginnering , IEEE Transactions.

Patel, A.B., Birla, M. and Nair, U. (2012) Addressing Big Data Problem Using Hadoop and Map Reduce, NIRMA University Conference on Engineering, pp. 1-5

Aditya B. Patel, Manashvi Birla, Ushma Nair, (6-8 Dec. 2012),”Addressing Big Data Problem Using Hadoop and Map Reduce”.

Jyothi Bellary, Bhargavi Peyakunta, Sekhar Konetigari “Hybrid Machine Learning Approach In Data Mining”, 2010 Second International Conference on Machine Learning and computing. Shiv Pratap Singh Kushwah, Keshav Rawat, Pradeep Gupta” Analysis and Comparison of Efficient Techniques of Clustering Algorithms in Data Mining” International Journal of Innovative.

Fayyad, U. Data Mining and Knowledge Discovery: Making Sense Out of IEEE Expert, v. 11, no. 5, pp. 20-25, October 1996.

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Published

2025-11-11

How to Cite

[1]
V. K. Gujare and P. Malviya, “A Novel Algorithm for Big Data Clustering”, Int. J. Comp. Sci. Eng., vol. 4, no. 8, pp. 38–40, Nov. 2025.

Issue

Section

Review Article