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An Efficient Web Server Log Analysis Using Genetic Algorithm-Based Preprocessing

  • Naresh Kumar Kar
  • Megha Mishra
  • Subhash Chandra Shrivastava
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Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 103)

Abstract

Popularity of web increases day by day, everything associated with daily life of human being all are connected to web and most of the people spending their time over the web through social networking web apps for their purchasing. Web server stores every activity of users in the form of logs, which contain very useful patterns, henceforth web server log analysis is the vital research area. Web log data analysis has primary step is preprocessing which is meant for dimensionality reduction because web log data is hefty in size and need to normalize the data for further cognitive analysis or other data analysis. Bulky data size degrades the performance of data analytic algorithm so there is necessity of an efficient algorithm for preprocessing over web server log data. In this paper, we put emphasis on data preprocessing. We have proposed the use of genetic algorithm for dimension reduction and normalization of input web server log data. Experimental result shows the data preprocessed data produces higher precision value, precision calculated using MATLAB 2016 classification learner tool.

Keywords

Genetic ROC TPR FNR Confusion matrix WM URL 

References

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Naresh Kumar Kar
    • 1
  • Megha Mishra
    • 1
  • Subhash Chandra Shrivastava
    • 1
  1. 1.Department of Computer Science and EngineeringRungta College of Engineering and TechnologyBhilaiIndia

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