1. 1. Roop Ranjan, Sameena Naaz and Neeraj Kaushik, “Web Miner: A Tool for Discovery of Usage Patterns From Web Data”, International Journal on Computer Science and Engineering (IJCSE), Vol. 5 No. 05 May 2013, pp. 286-293, ISSN: 0975-3397. 
   2. The W3C Technology Stack; “World Wide Web Consortium”, Retrieved April 21, 2012.
   3. Arvind K Sharma, P. C. Gupta,“Enhancing the Performance of the Website through Web Log Analysis and Improvement”, International Journal of Computer Science and Technology (IJCST) Vol. 3, Issue 4, Oct-Dec 2012.
   4. Huiping Peng, “Discovery of Interesting Association Rules Based on Web Usage Mining”, International Conference 2010.
   5. Cooley, R.,“Web Usage Mining: Discovery and Application of Interesting Patterns from Web data”, 2000.
   6. Liu, H., et al., “Combined mining of Web server logs and web contents for classifying user navigation patterns and predicting user‟s future requests”, Data and Knowledge Engineering, 2007, Vol. 61, Issue 2, pp. 304- 330.
   7. M. Spiliopoulou and L. C. Faulstich. Wum, “A web utilization miner”. In Proc. of EDBT WorkshopWebDB98, Valencia, Spain, March 1998.
   8. M. Malarvizhi, S. A. Sahaaya Arul Mary, “Preprocessing of Educational Institution Web Log Data for Finding Frequent Patterns using Weighted Association Rule Mining Technique”, European Journal of Scientific Research ISSN 1450-216X Vol.74 No.4 (2012), pp. 617- 633.
   9. Sanjay Madria, Sourav s Bhowmick, w. -k ng, e. P. Lim, “Research Issues in Web Data Mining”.
   10. A. Jebaraj Ratnakumar, “An Implementation of Web Personalization Using Web Mining Techniques”, Journal Of Theoretical And Applied Information Technology, 2005 - 2010 JATIT
   11. Tsuyoshi, M and Saito, K., “Extracting User‟s Interest for Web Log Data”, IEEE 2006, pp. 343-346, ISBN: 0-7695-2747-7