Advertisement

Analysis of Web Usage Patterns to Identify Most Frequently Accessed Web Page by Multiple Users

  • Priyanka VermaEmail author
  • Nishtha Kesswani
Conference paper
  • 8 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1122)

Abstract

All Data related to web sites that we access is stored in web logs. Increase in browsing these days has led to increase in size of these web log files. Web Mining is one technique that can be applied to these log files to mine navigational patterns. There are various types of web mining depending upon data mined Content, Usage or Structure. In this paper we focus on Mining of usage patterns: Web Usage Mining to discover most frequently accessed web page by multiple users after preprocessing of log file.

Keywords

Web Usage Patterns Navigation Log file Web Usage Mining 

References

  1. 1.
    Reddy, K.S., Partha Saradhi Varma, G., Babu, I.R.: Preprocessing the web server logs an illustrative approach for effective usage mining. ACM SIGSOFT Softw. Eng. Notes 37, 1–5 (2012)Google Scholar
  2. 2.
    Cooley, R., Mobasher, B., Srivastava, J.: Web mining: information and pattern discovery on the World Wide Web. In: Proceedings of Ninth IEEE International Conference, pp. 558–567 (1997)Google Scholar
  3. 3.
    Frias-Martinez, E., Karamcheti, V.: A customizable behavior model for temporal prediction of web user sequences. In: WEBKDD, pp. 66–85 (2002)Google Scholar
  4. 4.
    Huiying, Z., Wei, L.: An intelligent algorithm of data pre-processing in web usage mining. In: Proceedings of the 5th World Congress on Intelligent Control and Automation, pp. 3119–3223. IEEE (2004)Google Scholar
  5. 5.
    Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery: an overview. In: Advances in Knowledge Discovery and Data Mining, pp. 1–34. AAAI/MIT Press (1996)Google Scholar
  6. 6.
    Langhnoja, S., Barot, M., Mehta, D.: Pre-processing: procedure on web log file for web usage mining. Int. J. Emerg. Technol. Adv. Eng. 2(12), 419–423 (2012)Google Scholar
  7. 7.
    Suguna, R., et al.: User interest level based preprocessing algorithms using web usage mining. Int. J. Comput. Sci. Eng. (IJCSE) 5(09), 815–822 (2013)Google Scholar
  8. 8.
    Vijayashri, L., Madhuri, J.: Data preprocessing in web usage mining. In: Proceedings of International Conference on Artificial Intelligence and Embedded Systems (ICAIES 2012), Singapore, pp. 1–5 (2012)Google Scholar
  9. 9.
    Mobasher, B.: Web usage mining in web data mining exploring hyperlinks, contents, and usage data, Chicago, USA, Ch. 12, pp. 449–482. Springer, Heidelberg (2012)Google Scholar
  10. 10.
    Chitraa, V., Davamani, D., Selvdoss, A.: A survey on preprocessing methods for web usage data. Int. J. Comput. Sci. Inf. Secur. (IJCSIS) 7, 78–83 (2010)Google Scholar
  11. 11.
    Cooley, R., Mobasher, B., Srivastava, J.: Data preparation for mining world wide web browsing patterns. Knowl. Inf. Syst. 1, 1–27 (1999)CrossRefGoogle Scholar
  12. 12.
    Patil, P., Patil, U.: Preprocessing of web server log file for web mining. World J. Sci. Technol. 2, 14–18 (2012). Proceedings of National Conference on Emerging Trends in Computer Technology (NCETCT 2012)Google Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.IIS (deemed to be) UniversityJaipurIndia
  2. 2.Central UniversityAjmerIndia

Personalised recommendations