Mining for Web Engineering

  IJCOT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© - Issue 2011 by IJCTT Journal
Volume-2 Issue-2                           
Year of Publication : 2011
Authors :A. Venkata Krishna Prasad , Prof. S.Ramakrishna.

MLA

A. Venkata Krishna Prasad , Prof. S.Ramakrishna."Mining for Web Engineering"International Journal of Computer Trends and Technology (IJCTT),V2(2):634-639 Issue 2011 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract: - The main theme of the research paper is to identify the web engineering tasks from mining process. In this paper, all areas are studied that are basically required for web mining and web engineering tasks.

References-

[1] Ajith Abraham, “Business Intelligence from Web Usage Mining”, Department of Computer Science, Oklahoma State University, USA.
[2] Anupam Joshi and Pranam Kolari, “Web Engineering Column: Web Mining: Research and Practice”, IEEE Computing and Science and Engineering, July/August 2004 pp. 49-53.
[3] Athula Ginge and San Murugesan, “Web Engineering: A Methodology for Developing Scalable, Maintainable Web Applications”, Cutter IT Journal,Vol.14, No.7, July 2001, pp.:24-35.
[4] G.Sreedhar, Dr. A.A.Chari, Dr. V.V.Venkata Ramana, “A Qualitative and Quantitative Frame work for effective Web Site Design”, IJCA, Vol 2, May 2010, PP 48-56.
[5] Jiawei Han, Kevin Chen-Chuan Chang, “Data Mining for Web Intelligence”, IEEE Computer November, 2002 pp. 64-70.
[6] Martha Koutri and Sophia Daskalaki. “Improving Web Site Usability Through a Clustering Approach”, In Proceedings of the 10th International Conference on Human-Computer Interaction HCI, Crete, Greece, 2003, PP. 11-19.
[7] Tao Xie, Jian Pei, Ahmed E. Hassan “Mining Software Engineering Data”, 29th International Conference on Software Engineering, 2007, IEEE.
[8] Wingyan Chung “Designing Web-based Business Intelligence Systems: A Framework and Case Studies: In DESRIST”, February 24-25, California CA USA 2006, pp. 147 – 171.

Keywords— Web Mining, Web Engineering, Web site errors, Web objects, Web logs.