In the era of technological development, more and more data is being accumulated on daily basis. Therefore it is a challenge to process, store and manage those ever increasing size of data. Before processing, classification of large amount of files needed. In this paper the authors develop a method to classify large amount of unstructured big data files into a small number of groups, each containing structured data files. The objective is that after classification the classified groups will be a better form of resource to the concerned user for further processing.

Big data, r-train, identity tag, Classification, Unstructured data

[1] G. Noseworthy, Infographic: Managing the Big Flood of Big Data in Digital Marketing, 2012 http://analyzingmedia.com/2012/infographic-big-flood-of-big-data-in-digital-marketing.
[2] H. Moed, The Evolution of Big Data as a Research and Scientific Topic: Overview of the Literature, 2012, ResearchTrends, http://www.researchtrends.com
[3] Gartner, Big Data Definition, http://www.gartner.com/it-glossary/big-data.
[4] P. Zikipoulos, T. Deutsch, D. Deroos, Harness the Power of Big Data, 2012, http://www.ibmbigdatahub.com/blog/harness-power-big-data-book-excerpt.
[5] C. Zhu, Q. Li, L. Kong, and S. Wei, A combined index for mixed structured and unstructured data, Proc. - 2015 12th Web Inf. Syst. Appl. Conf. WISA 2015, pp. 217–222, 2016.
[6] Ahad, Mohd Abdul, Biswas, Ranjit, Comparing and Analyzing the Characteristics of Hadoop, Cassandra and Quantcast File Systems for Handling Big Data. Indian Journal of Science and Technology, [S.l.], 2017. ISSN 0974 -5645.
[7] Konstantin Shvachko, Hairong Kuang, Sanjay Radia, Robert Chansler, The Hadoop Distributed File System, IEEE (2010).
[8]Dhruba Borthakur, HDFS Architecture Guide, Apache Foundation https://hadoop.apache.org/docs/r1.2.1/hdfs_design.pdf, (2008).
[9] Md Tabrez Nafis, Ranjit Biswas, A Secure Clustering Technique for Unstructured and Uncertain Big Data. In Springer proceedings of 1st International Conference on Advanced Computing & Intelligent Engineering(ICACIE)(Springer),451,2016.
[10] Biswas, Ranjit., Atrain Distributed System (ADS): An Infinitely Scalable Architecture for Processing Big Data of Any 4Vs, in Computational Intelligence for Big Data Analysis Frontier Advances and Applications: edited by D.P. Acharjya, Satchidananda Dehuri and Sugata Sanyal, Springer International Publishing Switzerland 2015, Part-1, 1-53 (2015).
[11]Ranjit Biswas, r-Train (Train) : A New Flexible Dynamic Data Structure, INFORMATION : An International Journal (Japan), Vol.14(4) April’2011, page 1231-1246.
[12] Ranjit Biswas, Heterogeneous Data Structure R-Atrain, INFORMATION : An International Journal (Japan), Vol.15(2) February’2012, pp 879-902(2012) International Information Institute of Japan & USA).
[13]Jin, X., Wah, B.W., Cheng, X.,Wang, Y., Significance and Challenges of Big Data Research, Journal Of Big Data Research(Elsevier),2017.
[14] K. Thyagarajan, N. Vaishnavi, "Performance Study on Malicious Program Prediction Using Classification Techniques", International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.59-64, 2018.
[15]H. Kousar, B.R.P. Babu, "Efficient Map/Reduce secure data using Multiagent System", International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.144-149, 2018.