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IJSTR >> Volume 3- Issue 7, July 2014 Edition



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

Website: http://www.ijstr.org

ISSN 2277-8616



A Systematic Review On Mining Web Navigation Pattern Using Graph Based Techniques

[Full Text]

 

AUTHOR(S)

Hemraj K. Varachhia, Ankur N. Shah

 

KEYWORDS

Index Terms: web log repository, filtered data, recommendation, web usage graph, Apriori & Eclat, TSPs, via-link

 

ABSTRACT

Abstract: Today internet is widely used in every aspect of day to day life. People get more and more dependent on internet for getting any kind of information. Record of different web user’s web using pattern are get stored in web log repository, which are great source of knowledge about user’s navigation. With increasing the use of internet, number of web sites and web pages are increasing rapidly. So analyze and discovering user’s interesting patterns are necessary for web administrator and recommendation system. Web usage mining is a part of data mining. In this, mining techniques are applied to web data for finding user’s interesting patterns. That means in which patterns user want to access web pages and web-sites. In this review paper I reviewed several pattern reorganization techniques such as graph traversal algorithm, efficient sequential pattern mining algorithm, mining a web usage data mining graph. From this entire techniques graph traversal algorithm is best.

 

REFERENCES

[1] Yao-Te Wang, Anthony J.T.Lee, “Mining Web navigation patterns with a path traversal graph”, ELSEVIER(2011), pages (7112-7122)

[2] Dilip Sing Sisodia, Shrish Verma. “Web Usage Pattern Analysis Through Web Logs: A Review”, IEEE(2012), pages(49-53)

[3] Dheeraj Kumar Singh, Varsha Sharma, Sanjeev Sharam, “Graph based Approach for Mining Frequent Sequential Access Patterns of Web pages”, IJCA(2012) pages (33-37)

[4] Bina Kotiyal, et. al., “User Behavior Analysis in Web Log through Comparative Study of Eclat and Apriori” IEEE(2012) pages (421-426)

[5] Mirghani A. Eltahir, Anour F. A. Dafa-Alla, “Extracting Knowledge from Web Server Logs Using Web Usage Mining” IEEE(2013), pages(413-417)

[6] Mnaish Valera, Uttam Chuhan, “An Efficient Web Recommender System based on Approach of Mining Frequent Sequential Pattern from Customized Web Log Preprocessing”, IEEE(2013)