Skip to main content
SpringerLink
Log in

Web Usage Characterization for System Performance Improvement

  • Conference paper
  • First Online:
Information and Communication Technology for Development for Africa (ICT4DA 2017)

Abstract

Web usage mining discovers patterns of user behaviors from web log files. In this study web usage mining is employed to identify business-critical and non-business critical web traffics in University of Gondar. Apriori and FP tree algorithms are applied to extract the web browsing behavior in terms of frequently accessed sites along with their web traffics. Our research findings can be used as an input for bandwidth management and system performance improvement.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Vellingiri, J., Pandian, S.C.: Survey on web usage mining. Glob. J. Comput. Sci. Technol. 11(4) (2011)

    Google Scholar 

  2. Munilatha, R., Venkataramana, K.: A study on issues and techniques of web mining. Int. J. Comput. Sci. Mob. Comput. Mon. J. Comput. Sci. Inf. Technol. 3(5) (2014)

    Google Scholar 

  3. Madhak, N.N., Kodina, T.M., Jayesh N. Varnagar, R.C.R.: Web usage mining using association rule mining on clustered data for pattern discovery. Int. J. Data Min. Tech. Appl. 2(1) (2013)

    Google Scholar 

  4. Vijiyarani, S., Suganya, E.: Research issues in web mining. Int. J. Comput.-Aided Tech. (IJCAx) 2(3), 55–64 (2015)

    Google Scholar 

  5. Santhosh Kumar, B., Rukmani, K.V.: Implementation of web usage mining using apriori and FP growth algorithms. J. Adv. Netw. Appl. 1(6), 400–404 (2010)

    Google Scholar 

  6. Oskouei, R.J.: Identifying students behaviors related to internet usage patterns. IEEE Computer Science and Engineering Department Motilal Nehru National Institute Of Technology Allahabad (2010)

    Google Scholar 

  7. Amutha, K., Devapriya, M.: Web mining: a survey paper. Int. J. Comput. Trends Technol. (IJCTT) 4(9), 3038–3042 (2013)

    Google Scholar 

  8. Uma Maheswari, B., Sumathi, P.: A comparative study of rule mining based web usage mining algorithms. Int. J. Sci. Res. (IJSR) 4(11), 2540–2543 (2015)

    Article  Google Scholar 

  9. Parvatikar, S., Joshi, B.: Analysis of user behavior through web usage mining. Int. J. Comput. Appl. (09750–8887) 27–31 (2014)

    Google Scholar 

  10. Han, J., Kamber, M.: Data Mining: Concepts and Techniques. 2nd edn, pp. 243–246. Elsevier, Amsterdam (2006)

    Google Scholar 

  11. Kumar, R., Tomkins, A.: A characterization of online browsing behavior. In: International World Wide Web Conference Committee (IW3C2), 26–30 April 2010

    Google Scholar 

  12. Srivastava, J., Cooley, R.: Web usage mining: discovery and applications of usage patterns from web data. SIGKDD Explor. 1(2), 12 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Informatics, University of Gondar, Gondar, Ethiopia

    Alehegn Kindie & Adane Mamuye

  2. Department of Health Informatics, University of Gondar, Gondar, Ethiopia

    Biniyam Tilahun

Authors
  1. Alehegn Kindie
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adane Mamuye
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Biniyam Tilahun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alehegn Kindie .

Editor information

Editors and Affiliations

  1. Council for Scientific and Industrial Research, Pretoria, South Africa

    Fisseha Mekuria

  2. Information Technology, University of Turku, Turku, Finland

    Ethiopia Enideg Nigussie

  3. Dresden University of Technology, Dresden, Germany

    Waltenegus Dargie

  4. Aalto University, Helsinki, Finland

    Mutafugwa Edward

  5. Bahir Dar Institute of Technology, Bahir Dar, Ethiopia

    Tesfa Tegegne

Rights and permissions

Reprints and permissions

Copyright information

© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kindie, A., Mamuye, A., Tilahun, B. (2018). Web Usage Characterization for System Performance Improvement. In: Mekuria, F., Nigussie, E., Dargie, W., Edward, M., Tegegne, T. (eds) Information and Communication Technology for Development for Africa. ICT4DA 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 244. Springer, Cham. https://doi.org/10.1007/978-3-319-95153-9_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-95153-9_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95152-2

  • Online ISBN: 978-3-319-95153-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation