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Computational Intelligence in Data Mining—Volume 2 pp 383–393Cite as

Performance Analysis of Selected Data Mining Algorithms on Social Network Data and Discovery of User Latent Behavior

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 411))

Abstract

This paper is summery for experimental research work carried out on internet usage activities of students on social network sites. The summarized research work has proposed a novel and efficient method for discovery of user latent behavior from the student’s datasets. A comparison with existing standard method is also presented which show that the proposed approach is better on the basis of accuracy, error rates, time sharing etc. features.

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References

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Author information

Authors and Affiliations

  1. School of Computational Sciecnes, S.R.T.M. University, Nanded, 431606, MS, India

    Parag Bhalchandra, Santosh Khamitkar, Nilesh Deshmukh, Sakharam Lokhande, Satish Mekewad & Pawan Wasnik

  2. Department of Computer Science, New Model Degree College, Hingoli, MS, India

    Santosh Phulari

Authors
  1. Santosh Phulari
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  2. Parag Bhalchandra
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  3. Santosh Khamitkar
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  4. Nilesh Deshmukh
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  5. Sakharam Lokhande
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  6. Satish Mekewad
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  7. Pawan Wasnik
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Corresponding author

Correspondence to Santosh Phulari .

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Editors and Affiliations

  1. Department of Computer Science Engineering and Information Technology, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  2. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India

    Durga Prasad Mohapatra

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Phulari, S. et al. (2016). Performance Analysis of Selected Data Mining Algorithms on Social Network Data and Discovery of User Latent Behavior. In: Behera, H., Mohapatra, D. (eds) Computational Intelligence in Data Mining—Volume 2. Advances in Intelligent Systems and Computing, vol 411. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2731-1_36

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  • DOI: https://doi.org/10.1007/978-81-322-2731-1_36

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2729-8

  • Online ISBN: 978-81-322-2731-1

  • eBook Packages: EngineeringEngineering (R0)

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