Internet Surfing Prediction System using Association Rule Mining based on FP-Growth

A. Singh¹ , N. Jain²

Section:Research Paper, Product Type: Isroset-Journal
Vol.4 , Issue.4 , pp.1-6, Aug-2016

Online published on Sep 08, 2016

Copyright © A. Singh, N. Jain . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Web Usage mining is nascent field of research which deals with extraction of interesting knowledge from the web log files. This paper describes the recent works on the field of Web Usage Mining(WUM) it is for the benefit of research on the future request and personalization of web based information services. Web Usage Mining puts an effort to determine valuable information from the secondary data obtained from the communications of users with the web. WUM involves three steps, which includes Preprocessing, Pattern discovery and Pattern analysis.

Key-Words / Index Term :
Web Usage Mining Frequent Pattern Tree Association Rule Web Logs.

References :
[1]. R. Chourasia, P. Choudhary, "An Approach For Web Log Pre-Processing And Evidence Preservation For Web Mining", International Journal of Computer Sciences and Engineering, Vol.2, Issue.4, pp.210-216, 2014.
[2]. M. Spilopoulou, L.C. Faultstich, Wum, “AWeb utilization Miner”, The World Wide Web and Databases, Vol. 1950, pp,184-20, 1998.
[3]. J. Srivastav, R. Colley, M. Despanade, PN. Tan, “Web Usage Mining: Discovery and Application of Usage Pattern from Web Data”, ACM SIGKDD Explorations Newsletter, Volume.1, Issue.2, pp.12-23, 2000.
[4]. R. Cooley, B. Mobasher, J. Srivasta, “Web Mining: Information and pattern Discovery on theWorld WideWeb”, IEEE International Conference on tools with Artificial Intelligence,USA, pp.558-567, 1997.
[5]. O. Etzioni, “The world wide web Quagmire or gold mine”, Magazine Communications of the ACM, Vol.39 Issue.11, pp.65-68, 1996.
[6]. R. Das, L. Turkoglu, “ Creatingmeaningful data from web logs for improving the impressiveness of a website by using path analysis method”, Expert Systems with Applications, Vol.36, Issue.3, pp.6635–6644, 2009.
[7]. P. Weichbrth, M. Owoc, M. Pleszkum, “Web User Navigation Pattern Discovery from WWW Server Log Files”, Proceeding of the Federal Conference on Computer Science and Information Systems, Wroclaw, pp.1171-1176, 2012.
[8]. V. Sujatha, Punithavalli, “Improved User Navigation Pattern Preditions From Web Log Data ”, Procedia Engineering, Vol.30, pp.92-99, 2012.
[9]. G. Mansingh, L. Rao, KMO. Bryson, “Profilling Internet Banking users:A Knowledge discovery in data mining process model based approach” , Information Systems Frontiers, Vol.17, Issue.1, pp.193–215, 2015.
[10]. U. Patil, S. Pardeshi, “A Servey on User Future Request Prediction: Web Usage Mining”, International journal of Emerging Technology and advanced Engineering, Vol.2, Issue. 3, pp. 121-124, 2012.