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Effective Web Usage Mining to Extract the Knowledge for Modelling the E-Commerce Website

K. Rajeshwari, C. Vinothini


World Wide Web became a bilateral medium for sharing the information. Web mining utilizes data mining techniques to extract the knowledge from web data. To extract the interesting pattern from server log record, Web Usage Mining is used. There are four stages carried out in this paper such as data collection, preprocessing, extraction and analysis. In this paper, three diverse algorithms used for clustering, association rule, and subgroup discovery mining methods. Eventually, analysis has been done based on the extraction of each algorithm. The results obtained will be considered for efficient modeling of the e-commerce website.


Web Usage Mining, Clustering, Association Rule Mining, Subgroup Discovery.

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Agrawal, R., Imieliski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. In Proceedings of the 1993 ACM SIGMOD international conference on management of data (pp. 207–216). ACM Press

Arun Singh, Avinav Pathak, Dheeraj Sharma. Web Usage Mining: Discovery of Mined Data Patterns and their Applications. International Journal of Computer Science and Management Research Volume 2 Issue 5 May 2013 ISSN 2278-733X.

Carmona C, González, P Del Jesus, M. J., & Herrera, F. (2010). NMEEF- SD: Non-dominated multi-objective evolutionary algorithm for extracting fuzzy rules in subgroup discovery. IEEE Transactions on Fuzzy Systems, 18, 958–970.

C.J. Carmona , S.Ramírez -Gallego , F. Torres , E. Bernal, M.J. del Jesus , S. García(2012). Web usage mining to improve the design of an e-commerce website: Expert Systems with Applications 39 (2012) 11243–11249.

Carmona, C. J., González, P., Del Jesus, M. J., Navío, M., & Jiménez, L. (2011).Evolutionary fuzzy rule extraction for subgroup discovery in a psychiatric emergency department. Soft Computing, 15, 2435–2448.

Deb, K., Pratap, A., Agrawal, S., & Meyarivan, T. (2002). A fast and elitist Multi-objective genetic algorithm: NSGA-II. IEEE Transactions Evolutionary Computation, 6, 182–197.

Herrera, F., Carmona, C. J., González, P., & Del Jesus, M. J. (2011). An overview on subgroup discovery: Foundations and applications. Knowledge and Information Systems, 29, 495–525

Liao S. H., Chen, Y, Lin, Y. T (2011).Mining customer knowledge to implement online shopping and home delivery for hypermarkets. Expert Systems with Applications, 38, 3982–3991

Lloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28, 129–137.

MacQueen, J. B. (1967). Some methods for classification and analysis of multivariate observations. In Proceedings of 5th Berkeley symposium on mathematical statistics and probability (pp. 281–297).

Olatz Arbelaitz , Ibai Gurrutxaga, Aizea Lojo, Javier Muguerza, Jesús Maria Pérez, Iñigo Perona(2013).Web usage and content mining to extract knowledge for modeling the users of the Bidasoa Turismo website and to adapt it. Expert Systems with Applications xxx (2013) xxx–xxx.

P.Nithya, Dr. P.Sumathi. A Survey on Web Usage Mining: Theory and Applications. International Journal, Computer Technology & Applications, Volume 3 (4), 1625-1629.

Rajeshwari.K, Vinothini.c (2013).A survey on web usage mining in the field of e-commerce. Journal of Computing Technologies (2278 – 3814) Volume 2 Issue 9.

Soares, C., Peng, Y., Meng, J., Washio, T., & Zhou, Z. H. (Eds.). (2008). Applications of data mining in e-business and finance. Frontiers in artificial intelligence and applications. IOS Press.

Xuejun Zhang, John Edwards , Jenny Harding(2007).Personalized online sales using web usage data mining.Computers in Industry 58 (2007) 772–782.

Yu-Shiang Hung , Kuei-Ling B. Chen , Chi-Ta Yang, Guang-Feng Deng(2012).Web usage mining for analyzing elder self-care behavior patterns .Expert Systems with Applications 40 (2013) 775–783.


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