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Mar 6, 2015
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Abstract

Web usage mining is the third category in the web mining and it is the process of extracting useful information from the server logs. It is valuable not only to the businesses using online marketing, but also to the e-business. This types of web mining is used to gather the important information from customers visiting the site. The companies can study visitors activities through web analysis. This process is used to find out what users are looking for on the internet. In this some users might be looking for the textual data and some users might be looking for the multimedia data. Usage mining is classified into different kinds of data. Web server data, application server data and application level data. First, In web server data the user logs are collected by the web server. Second, The key feature of the application server data is the ability to track the various kinds of business events and log them in the application server logs. Finally, application level data is used to define an new kinds of events in an application.

Keywords: server logs, web analysis, web server data, application server data, application level data       

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How to Cite
S.Priyadharshini, S. (2015). A Survey on Web Usage Mining. International Journal of Emerging Trends in Science and Technology, 2(03). Retrieved from http://igmpublication.org/ijetst.in/index.php/ijetst/article/view/529

References

1. Manoj Manuja and Deepak Garg, Semantic web mining of Un-structured Data: Challenges and Opportunities, International Journal of Engineering, 5(3) ,2011, 268-276.
2. Jing Wang, Ying Liu, Lin Zhou, Yong Shi, and Xingquan Zhu, Pushing frequency constraint to utility Mining Model, ICCS Springer-Verlag Berlin Heidlberg, LNCS 4489, 2007, 685-692
3. Nina, S.P., Rahman, M., Bhuiyan, K.I. and Ahmed, K., "Pattern Discovery of Web Usage Mining", International Conference on Computer Technology and Development, Vol. 1, Pp.499- 503, 2009.
4. ShaileyMinocha, Nicola Millard, Lisa Dawson, “Integrating Customer Relationship Management Strategies in (B2C) ECommerce Environments”, IFIP Conference on HumanComputer Interaction- INTERACT, 2003.
5. Chaoyang Xiang, Shenghui He and Lei Chen, “A Studying System Based On Web Mining”, IEEE International Symposium On Intelligent Ubiquitous Computing and Education, pp.433-435, 2009.
6. Nasraoui, O., Soliman, M., Saka, E., Badia, A. and Germain, R., "A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Sites", IEEE Transactions on Knowledge and Data Engineering, Vol. 20, No. 2, Pp. 202-215, 2008.
7. Adda, M., Valtchev, P., Missaoui, R. and Djeraba, C., "Toward Recommendation Based on Ontology-Powered Web-Usage Mining", IEEE Internet Computing, Vol. 11, No. 4, Pp. 45-52, 2007.
8. Etminani, K., Delui, A.R., Yanehsari, N.R. and Rouhani, M., "Web Usage Mining: Discovery of the Users' Navigational Patterns Using SOM", First International Conference on Networked Digital Technologies, Pp.224-249, 2009.