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Development of a model for studying Web user activity by an analysis of Web traffic

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Abstract

The article considers methods of intelligent data analysis (data mining) used in problems involved in the analysis of Web traffic, and also considers the application of the method of cluster analysis and a newly developed model for the study of Web user activity.

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References

  1. Bartolini, G., Web Usage Mining and Discovery of Association Rules from http Servers Logs, www.prato.linux.it/:_gbartolini/en/view-a/2/pdf/wum.pdf (2001).

  2. Baglioni, M., Ferrara, U., Romeil, A., Ruggieri, S., and Turini, F., Preprocessing and Mining Web Log Data for Web Personalization, www.di/unipi.it/:_ruggieri/Papers/aiia2003.pdf, 2003.

  3. Wanga, X., Abrahamb, A., and Smitha, K.A., Intelligent Web Traffic Mining and Analysis, J. Network Comp. Appl., 2004, vol. 28, p. 147–165.

    Article  Google Scholar 

  4. Rabin, D., Study Log Journals, Seti i Sist. Svyazi, no. 1 (121); http://ccc.ru/magazine/depot/05_01/read.html?htm, 2005.

  5. Ivancsy, R. and Vajk, I., Different Aspects of Web Log Mining, in 6th Intern. Symp. Hungarian Researchers on Computational Intelligence, Budapest, Nov., 2005.

  6. Ivancsy, R. and Vajk, I., Frequent Pattern Mining in Web Log Data, www.bmf.hu/journal/Ivancsy_Vajk_5.pdf, 2006.

  7. Chakrabarti, S., Data Mining for Hypertext: A Tutorial Survey, SIGKDD: SIGKDD Explorations: Newsletter Special Interest Group (SIG) on Knowledge Discovery and Data Mining, ACM, vol. 1, no. 2, pp. 1–11, 2000.

    Google Scholar 

  8. Dyuk, V.A. and Samoilenko, A.V., Data Mining, Uchebnyi Kurs (Data Mining. Textbook), St. Petersburg: Piter, 2001.

    Google Scholar 

  9. Kosala, R. and Blockeel, H., Web Mining Research: A Survey, SIGKKD Explorations, vol. 2(1), July, 2000.

  10. Fu, Y., Sandhu, K., and Shih, M.Y., Clustering of Web Users Based on Access Patterns, in Proc. ACM SIGKDD Intern. Conf. Knowledge Discovery and Data Mining (KDD(99) Workshop on Web Mining), San Diego (U.S.), vol. 5, pp. 560–567, 1999.

    Google Scholar 

  11. Metody klusternogo analiza (Methods of Cluster Analysis), http://www.intuit.ru/department/database/datamining, 2006.

  12. Morzy, T., Wojciechowski, M., and Zakrzewicz, M., Web Users Clustering, in Proc. 15th Intern. Symp. Comp. Inform. Sci., Istanbul (Turkey), pp. 374–382, 2000.

  13. Xie, Y. and Phoca, V.V., Web User Clustering from Access Log Using Belief Function, Proc. 1st Intern.Conf. Knowledge Capture (K-CAP 01), ACM Press, 2001, pp. 202–208.

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Correspondence to F. F. Yusifov.

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Original Russian Text © R.M. Alyguliev, F.F. Yusifov, 2007, published in Avtomatika i Vychislitel’naya Tekhnika, 2007, No. 4, pp. 73–77.

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Alyguliev, R.M., Yusifov, F.F. Development of a model for studying Web user activity by an analysis of Web traffic. Aut. Conrol Comp. Sci. 41, 232–235 (2007). https://doi.org/10.3103/S0146411607040074

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  • DOI: https://doi.org/10.3103/S0146411607040074

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