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Stratified Sampling-Based Data Reduction and Categorization Model for Big Data Mining

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Communication and Intelligent Systems (ICCIS 2019)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 120))

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Abstract

Nowadays, communication, digital and real-time-based applications are widely used by the user. These types of technologies change the speed of data generation, the format of data, storing natures, and their management. The common challenges of big data mining are related to the data volume, and data volume is indirectly related to the variety of data and data velocity. The volume-related challenges isolated by the big data analysis strategies are divide-and-conquer, feature selection, parallel processing, granular computing, incremental learning, and sampling. These big data analysis strategies reduce the data for the data mining and also categorized the variety. This paper used sampling for data reduction and categorization through stratified sampling because stratified sampling has capability data categorization in efficient ways. From a theoretical, practical, and the existing research perspective, the paper focuses on big data and characteristics, big data mining, big data reduction strategies, sampling techniques for big data, and design the model for data reduction and categorization through stratified sampling, and this model describes the new data mining technique based on stratified sampling which is known as stratified sampling-based (data mining algorithm name). The data reduction and categorization model is explained by using the partitioning-based K-means clustering algorithm, which is known as the SSBKM through this model.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Applications, Dr. HariSingh Gour Vishwavidyalaya, Sagar, Madhya Pradesh, India

    Kamlesh Kumar Pandey & Diwakar Shukla

Authors
  1. Kamlesh Kumar Pandey
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  2. Diwakar Shukla
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Editor information

Editors and Affiliations

  1. South Asian University, New Delhi, Delhi, India

    Jagdish Chand Bansal

  2. Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, Rajasthan, India

    Mukesh Kumar Gupta

  3. Department of Computer Science and Engineering, Rajasthan Technical University, Kota, Rajasthan, India

    Harish Sharma

  4. Indian Institute of Information Technology, MNIT Campus, Jaipur, Rajasthan, India

    Basant Agarwal

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Pandey, K.K., Shukla, D. (2020). Stratified Sampling-Based Data Reduction and Categorization Model for Big Data Mining. In: Bansal, J., Gupta, M., Sharma, H., Agarwal, B. (eds) Communication and Intelligent Systems. ICCIS 2019. Lecture Notes in Networks and Systems, vol 120. Springer, Singapore. https://doi.org/10.1007/978-981-15-3325-9_9

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