Web Log Analysis Tools: At a Glance

  • Vinod KumarEmail author
  • Ramjeevan Singh Thakur
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 34)


Current cyber space is now flooding with huge number of Web sites, and the analysis of the Web sites is extremely needed to extract the gainful information. For the analysis task on Web sites’ log file, there exist various log analysis tools. However, the impeccable trouble emerges in determination of suitable tools. This work provides an examination of open source and commercial toolsets available for the analysis and its basic internal analysis process; the study will provide many choices to pick from when deciding a toolset to manage and analyze log data. The paper will help to review the set of tools currently available and positively hook the right tool to get started on analyzing logs files.


Web log analyzer Web usage mining Web log analysis Web log 



This work was supported by the Dept. of Computer Application, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, India


  1. 1.
    Etzioni, O.: The world wide web: quagmine or gold mine. Commun. ACM 39(11), 65–68 (1996)CrossRefGoogle Scholar
  2. 2.
    Mobasher, B.: Web Usage Mining and Personalization. CRC Press, LLC (2005)Google Scholar
  3. 3.
    Carmona, C.J., et al.: Web usage mining to improve the design of an e-commerce website: Expert Syst. Appl. 39, 11243–11249 (2012)CrossRefGoogle Scholar
  4. 4.
    Anitha, V., Isakki, P.: A survey on predicting user behavior based on web server log files in a web usage mining. In: International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE’16), Kovilpatti, India, pp. 1–4 (2016)Google Scholar
  5. 5.
    Kumar, V., Thakur, R.S.: Exploring behavior of visitors activity at granular level from web log data using deep log analyzer. Int. J. Syst. Softw. Eng. 4(1), 16–26 (2016)Google Scholar
  6. 6.
    Wongsirichot, T., Sukpisit, S., Hanghu, W.: A preliminary analysis of web usage behaviors from web access log files. Proc. Int. Conf. Soft Comput. Tech. Eng. Appl. 250, 325–332 (2013)Google Scholar
  7. 7.
    Kumar, V., et al.: A brief investigation on Web Usage Mining Tools (WUM). Saudi J. Eng. Technol. 2(1), 1–11 (2017)Google Scholar
  8. 8.
    Bhuvaneswari, S., Anand, T.: A comparative study of different log analyzer tools to analyze user behaviors. Int. J. Recent Innov. Trends Comput. Commun. 3(5), 2997–3002 (2015). ISSN: 2321-8169Google Scholar
  9. 9.
    Kaur, N., Aggarwal, H.: A comparative study of WUM Tools to analyze user behaviour pattern from web log data. Int. J. Adv. Eng. Res. (IJAER) 10(4), 123–138 (2015). ISSN: 2231-5152Google Scholar
  10. 10.
    Dhandi, M., Chakrawarti, R.K.: A comprehensive study of web usage mining. In: 2016 Symposium on Colossal Data Analysis and Networking (CDAN), Indore, pp. 1–5 (2016)Google Scholar
  11. 11.
    Joshila Grace, L.K., Maheswari, V., Nagamlai, D.: Web log data analysis and mining. Adv. Comput. Commun. Comput. Inf. Sci. 133, 459–469 (2011)Google Scholar
  12. 12.
    Lakshmi, N., Rao, R.S., Reddy, S.S.: An overview of preprocessing on web log data for web usage analysis. Int. J. Innov. Technol. Explor. Eng. (IJITEE) 2(4), 274–279 (2013). ISSN: 2278-3075Google Scholar
  13. 13.
    Habin, L., Vlado, K.: Combining mining of web server logs and web content for classifying user’s navigation pattern and predicting users future request. J. Data Knowl. Eng. 61, 304–330 (2007)CrossRefGoogle Scholar
  14. 14.
    Li, Y., Feng, B., Mao, Q.: Research on path completion technique in web usage mining. In: International Symposium on Computer Science and Computational Technology (2008)Google Scholar
  15. 15.
    Adeniyi, D.A., Wei, Z., Yongquan, Y.: Automated web usage data mining and recommendation system using K-Nearest Neighbor (KNN) classification method. Appl. Comput. Inform. 12, 90–108 (2016)CrossRefGoogle Scholar
  16. 16.
    Tiwari, V., Thakur, R.S.: Contextual snowflake modelling for pattern warehouse logical design. Sadhana Acad. Proc. Eng. Sci. 40, 15–33 (2015)Google Scholar
  17. 17.
    Tiwari, V., Thakur, R.S.: Pattern warehouse: context based modeling and quality issues. Proc. Natl. Acad. Sci. India Sect. A: Phys. Sci. 86, 417–431 (2016)CrossRefGoogle Scholar
  18. 18.
    Cooley, R., Mobasher, B., Srivastava, J.: Web mining: information and pattern discovery on the World Wide Web. In: Proceedings of Ninth IEEE International Conference Tools with Artificial Intelligence, pp. 558–567 (1997)Google Scholar
  19. 19.
    Facca, F.M., Lanzi, P.L.: Mining interesting knowledge from weblogs: a survey. Data Knowl. Eng. 53(3), 225–241 (2005)CrossRefGoogle Scholar
  20. 20.
    Federico, M.F., Pier, L.L.: Mining interesting knowledge from weblog: a survey. J. Data Knowl. Eng. 53, 225–241 (2005)CrossRefGoogle Scholar
  21. 21.
    Iváncsy, R.: Frequent pattern mining in web log data. Acta Polytechnica Hungarica 3(1) (2006)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer ApplicationsMaulana Azad National Institute of TechnologyBhopalIndia

Personalised recommendations