Research on the Mechanism of Web Data Mining in Electronic Commerce Application

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Abstract:

At present, the growth of the Internet has brought us a vast amount of information that we can hardly deal with. To solve the flood of information, various data mining systems have been created to assist and augment this natural social process. Data minig recommender systems have been developed to automate the recommendation process. Data mining recommender systems can be found at many electronic commerce applications. In this paper, a recommendation mechanism of web data mining in electronic commerce application is given. Then, presents the workflow of the web data mining in electronic commcer. Lastly, the usage of the tools of web data mining is described.

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3003-3006

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November 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Songjie Gong, A Collaborative Filtering Recommendation Algorithm Based on Trust Network and Trust Factor, Journal of Convergence Information Technology, Vol. 8, No. 5, p.1111 ~ 1118, 2013. 03.

DOI: 10.4156/jcit.vol8.issue5.129

Google Scholar

[2] Songjie Gong, Research on Attack on Collaborative Filtering Recommendation Systems, AISS: Advances in Information Sciences and Service Sciences, Vol. 5, No. 10, p.938 ~ 946, 2013. 05.

DOI: 10.4156/aiss.vol5.issue10.110

Google Scholar

[3] Xue, G., Lin, C., & Yang, Q., et al. Scalable collaborative filtering using cluster-based smoothing. In Proceedings of the ACM SIGIR Conference 2005 p.114–121.

Google Scholar

[4] D. Bridge and J. Kelleher, Experiments in sparsity reduction: Using clustering in collaborative recommenders, in Procs. of the Thirteenth Irish Conference on Artificial Intelligence and Cognitive Science, p.144–149. Springer, (2002).

DOI: 10.1007/3-540-45750-x_18

Google Scholar

[5] J. Kelleher and D. Bridge. Rectree centroid: An accurate, scalable collaborative recommender. In Procs. of the Fourteenth Irish Conference on Artificial Intelligence and Cognitive Science, pages 89–94, (2003).

Google Scholar

[6] Songjie Gong, Liping Zeng, The Solution of Safety of Electronic Cash in E-Commerce under Cloud Computing Environment, Advanced Materials Research, Vol. 989, pp: 4314-4317, (2014).

DOI: 10.4028/www.scientific.net/amr.989-994.4314

Google Scholar

[7] Songjie Gong, Research on the Growth Mechanism of High-Skilled System in Computer Science and Technology, Applied Mechanics and Materials, Vol. 513, pp: 2748-2751, (2014).

DOI: 10.4028/www.scientific.net/amm.513-517.2748

Google Scholar