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IJSTR >> Volume 9 - Issue 2, February 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Data Analytics For Web Structure Mining In Business Website

[Full Text]



Sathish Kumar G, Ramya R, Dinesh P S, Prabha Devi D, Janani A P



World Wide Web, Web Mining, Patterns, Hits, Nodes, Hyperlink, Document Object Model.



The huge amount of information is available in the World Wide Web (WWW) which creates the interesting factor for web mining. The access pattern of the webpages or websites, properties of the documents, behavior of the distinct customers can be analyzed by the web mining methods. Web miner software is employed to discover the similar patterns in the websites and is used to certify the information which is extracted from the pages. Our focus is to enhance the profit by web services in business domains. We have performed the algorithmic strategies for the effective implementation of our proposed technique. Our objective is to find the webpages as a widespread or popular webpages by using the Hit counts and the number of advertisements in that particular webpage.



[1] Dr. S. P. Victor, Mr. M. Xavier Rex , “ Analytical Implementation of Web Structure Mining Using Data Analysis in Educational Domain”, International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 4, pp. 2552-2556, 2016.
[2] Baraglia, R. Silvestri, F. "Dynamic personalization of web sites without user intervention", In Communication of the ACM 50(2): 63-67,2007.
[3] Cooley, R. Mobasher, B. and Srivastave, J. “Web Mining: Information and Pattern Discovery on the World Wide Web” In Proceedings of the 9th IEEE International Conference on Tool with Artificial Intelligence,1997.
[4] Cooley, R., Mobasher, B. and Srivastava, J. “Data Preparation for Mining World Wide Web Browsing Patterns”, Journal of Knowledge and Information System, Vol. 1, Issue. 1, pp. 5–32, 1999.
[5] Costa, RP and Seco, N. “Hyponymy Extraction and Web Search Behavior Analysis Based On Query Reformulation”, 11th Ibero-American Conference on Artificial Intelligence, 2008.
[6] Kohavi, R., Mason, L. and Zheng, Z. “Lessons and Challenges from Mining Retail E- commerce Data” Machine Learning, Vol 57, pp. 83– 113, 2004.
[7] Lillian Clark, I-Hsien Ting, Chris Kimble, Peter Wright, Daniel Kudenko"Combining ethnographic and clickstream data to identify user Web browsing strategies" Journal of Information Research, Vol. 11 No. 2, 2006.
[8] Eirinaki, M., Vazirgiannis, M. "Web Mining for Web Personalization", ACM Transactions on Internet Technology, Vol. 3, No. 1, 2003.
[9] Mobasher, B., Cooley, R. and Srivastava, J. “Automatic Personalization based on web usage Mining” Communications of the ACM, Vol. 43, No. 8, pp. 142–151, 2000.
[10] Mobasher, B., Dai, H., Luo, T. and Nakagawa, M. “Effective Personalization Based on Association Rule Discover from Web Usage Data” In Proceedings of WIDM 2001, Atlanta, GA, USA, pp. 9–15, 2001.
[11] Nasraoui O., PetenesC.,"Combining Web Usage Mining and Fuzzy Inference for Website Personalization", in Proc. of WebKDD 2003 – KDD Workshop on Web mining as a Premise to Effective and Intelligent Web Applications, Washington DC, p. 37,2003.