Web Usage Minning using Patterns with Different Algorithm

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Abstract

Web usage mining is a part of data mining. Data usage mining is divided into three parts 1) Data content mining 2) Data structured mining 3) Data usage mining. In this paper I am discussing about log files which are used in data usage mining. Log files are used to store user’s activity in web server using websites. So that websites can be improved by gathering user data. Web usage mining having three sub parts which is reprocessing, data discovery and data analysis. Further, in this paper, details about web log files are discussed. Three algorithms are discussed which are used for patterns of log files. There comparison is showed in this paper with the help of graphs.

Publisher

VFAST

Reference15 articles.

1. Agrawal, R., & Srikant, R. (1994, September). Fast algorithms for mining association rules. In Proc. 20th int. conf. very large data bases, VLDB (Vol. 1215, pp. 487-499).

2. Mannila, H., Toivonen, H., & Verkamo, A. I. (1995, August). Discovering frequent episodes in sequences extended abstract. In 1st Conference on Knowledge Discovery and Data Mining.

3. Kumar, B. S., & Rukmani, K. V. (2010). Implementation of web usage mining using APRIORI and FP growth algorithms. Int. J. of Advanced networking and Applications, 1(06), 400-404.

4. Becuzzi, P., Coppola, M., & Vanneschi, M. (1999, August). Mining of Association Rules in Very Large Databases: A Structured Parallel Approach⋆. In European Conference on Parallel Processing (pp. 1441-1450). Springer, Berlin, Heidelberg.

5. Langhnoja, S. G., Barot, M. P., & Mehta, D. B. (2013). Web usage mining using association rule mining on clustered data for pattern discovery. International Journal of Data Mining Techniques and Applications, 2(01), 144.

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