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Statistical Survey of Data Mining Techniques: A Walk-Through Approach Using MongoDB

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International Conference on Innovative Computing and Communications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 56))

Abstract

Big data is a term used for management of large, unstructured and complex data. It is used to organize data such that it is easy to read and understand. In today’s world of digitization, it becomes important to track the growth and evolution of data mining techniques. This paper makes an effort in this direction as thorough and in-depth study has been carried out of several mining techniques. Also to show the effectiveness of data mining techniques, simulation has been carried out of the real-time dataset in MongoDB.

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Author information

Authors and Affiliations

  1. USIC&T, GGSIP University, New Delhi, India

    Samridhi Seth & Rahul Johari

Authors
  1. Samridhi Seth
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  2. Rahul Johari
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Corresponding author

Correspondence to Samridhi Seth .

Editor information

Editors and Affiliations

  1. Department of Computer Application, RCC Institute of Information Technology, Kolkata, West Bengal, India

    Siddhartha Bhattacharyya

  2. Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  3. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Deepak Gupta

  4. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Ashish Khanna

  5. Department of Information Technology, RCC Institute of Information Technology, Kolkata, West Bengal, India

    Indrajit Pan

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Seth, S., Johari, R. (2019). Statistical Survey of Data Mining Techniques: A Walk-Through Approach Using MongoDB. In: Bhattacharyya, S., Hassanien, A., Gupta, D., Khanna, A., Pan, I. (eds) International Conference on Innovative Computing and Communications. Lecture Notes in Networks and Systems, vol 56. Springer, Singapore. https://doi.org/10.1007/978-981-13-2354-6_17

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