A Survey on Web Page Recommendation and Data Preprocessing
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Abstract
In today’s era, as we all know internet technologies are growing rapidly. Along with this, instantly, Web page recommendations are also improving. The aim of a Web page recommender system is to predict the Web page or pages, which will be visited from a given Web-page of a website. Data preprocessing is one basic and essential part of Web page recommendation. Data preprocessing consists of cleanup and constructing data to organize for extracting pattern. In this paper, we discuss and focus on Web page Recommendation and role of data preprocessing in Web page recommendation, considering how data preprocessing is related to Web page recommendation.
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References
Ben Schafer, Joseph A. Konstan, and John T. Riedl, “Recommender Systems for the Web”.
Vijayashri Losarwar et al., “Data Preprocessing in Web Usage Mining” International Conference on Artificial Intelligence and Embedded Systems July 15-16, 2012 Singapore.
Naga Lakshmi et al., “An Overview of Preprocessing on Web Log Data for Web Usage Analysis”, International Journal of Innovative Technology and Exploring Engineering ISSN: 2278-3075, Volume-2, Issue-4, March 2013.
Mitali Srivastava, Rakhi Garg, “Preprocessing Techniques in Web Usage Mining: A Survey”.
J. Manuel Adán-Coello, C. M. Tobar, Y. Yuming, “Improving the Performance of Web Service Recommenders Using Semantic Similarity”. In JCS&T Vol. 14, No. 2, October 2014.
Sabanaz S. Peerzade, Vanita D. Jadhav, “A Review on Web Service Recommendation System Using Collaborative Filtering”, Volume 3, Issue 3, March 2015.
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.
“A Survey on Preprocessing Methods for Web Usage Data”, (IJCSIS) International Journal of Computer Science and Information Security, Vol. 7, No. 3, 2010.
R. Cooley, B. Mobasher, J. Srivastav (1999), “Data preparation for mining world wide web browsing pattern” in Journal of Knowledge and Data Engineering Workshop, IEEE, Vol.1 .
Yan LI, Boqin FENG and Qinjiao MAO, “Research on Path Completion Technique in Web Usage Mining”, IEEE International Symposium on Computer Science and Computational Technology, pp. 554-559, 2008. 11. Ling Zheng, Hui Gui and Feng Li, “Optimized Data Preprocessing Technology For Web Log Mining”, IEEE International Conference on Computer Design and Applications, pp. VI-19-VI-21, 2010.
JING Chang-bin and Chen Li, “Web Log Data Preprocessing Based on Collaborative Filtering”, IEEE 2nd International Workshop on Education Technology and Computer Science, pp.118-121, 2010.
Fang Yuankang et al., “A Session Identification Algorithm Based on Frame Page and Page threshold”, IEEE Conference, pp.645- 647, 2010.
Huiping Peng, “Discovery of Interesting Association Rules Based on Web Usage Mining”, IEEE Conference, pp.272-275, 2010.