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International Conference on Distributed Computing and Internet Technology

ICDCIT 2015: Distributed Computing and Internet Technology pp 443–447Cite as

Data Mining on ICT Usage in an Academic Campus: A Case Study

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8956))

Abstract

Nowadays, every higher education institution needs to assess the degree of utilisation of Information and Communication Technology (ICT) facilities installed in the campus. This study is based on the responses collected from the student and research communities via survey on ICT in the University of Burdwan. Data mining methodologies – Fuzzy-Rough Feature Selection (FRFS) to reduce the dimensions of survey dataset and subsequently different classification techniques such as J48, JRip, QuickRules Fuzzy-Rough rule induction, Fuzzy Nearest Neighbour, Fuzzy Rough Nearest Neighbour and Vaguely Quantified Nearest Neighbour (VQNN) are applied on this resultant dataset to build model for potential knowledge extraction. Fuzzy-Rough Feature Selection (FRFS) and then different classification algorithms are applied using WEKA 3.7.9 for analysis of the reduced dataset.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Burdwan University, Burdwan, India

    Ajay Auddy & Sripati Mukhopadhyay

Authors
  1. Ajay Auddy
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  2. Sripati Mukhopadhyay
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Editor information

Editors and Affiliations

  1. School of Technology and Computer Science, Tata Institute of Fundamental Research, Homi Bhabha Road, Colaba, 400005, Mumbai, India

    Raja Natarajan

  2. Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, 781039, Guwahati, India

    Gautam Barua

  3. Department of Computer Science,, Berhampur University, 760007, Berhampur, Odisha, India

    Manas Ranjan Patra

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Auddy, A., Mukhopadhyay, S. (2015). Data Mining on ICT Usage in an Academic Campus: A Case Study. In: Natarajan, R., Barua, G., Patra, M.R. (eds) Distributed Computing and Internet Technology. ICDCIT 2015. Lecture Notes in Computer Science, vol 8956. Springer, Cham. https://doi.org/10.1007/978-3-319-14977-6_48

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  • DOI: https://doi.org/10.1007/978-3-319-14977-6_48

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14976-9

  • Online ISBN: 978-3-319-14977-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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