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Published in:   Vol. 1 Issue 1 Date of Publication:   June 2012

Hierarchical Frequent Pattern Analysis of Web Logs for Efficient Interestingness Prediction

G. Sudhamathy,C. Jothi Venkateswaran

Page(s):   19-23 ISSN:   2278-2397
DOI:   10.20894/IJWT.104.001.001.006 Publisher:   Integrated Intelligent Research (IIR)


  1. Kannan, S., & Bhaskaran, R,   "Association rule pruning based on interestingness measures with clus-tering",   International Journal of Computer Science Issues,    ,2009
    View Artical

  2. Liqiang Geng and Howard J. Hamilton,   "Interestingness Measures for Data Mining: A Survey",   ACM Computing Surveys   ,Vol.38   ,2006
    View Artical

  3. P. Tan, V. Kumar, and J. Srivastava,   "Selecting the Right Interestingness Measure for Association Patterns",   Army High Performance Computing Research Center   ,2002
    View Artical

  4. Liaquat Majeed Sheikh, Basit Tanveer, Syed Mustafa Ali Hamdani,   "Interesting Measures for Mining Association Rules",   In Proceedings of INMIC 2004. 8th international Mu   ,2004
    View Artical

  5. Tianyi Wu, Yuguo Chen, and Jiawei Han,   "Association Mining in Large Databases: A Re-Examination of Its Measures",   In Proceedings of PKDD 11th European Conference on   ,2007
    View Artical

  6. R. Iv?ncsy and I. Vajk,   "Time- and Memory-Efficient Frequent Itemset Discovering Algorithm for Association Rule Mining",   International Journal of Computer Applications in
    View Artical

  7. Huang, X,   "Comparison of interestingness measures for web usage mining: An empirical study",   International Journal of Information Technology &    ,2007
    View Artical

  8. Iv?ncsy, R., & Vajk, I.,   "Frequent pattern mining in web log data.",   Journal of Applied Sciences at Budapest Tech Speci   ,2008
    View Artical

  9. Jaroszewicz , S., & Simovici, D. A,   "Pruning redundant association rules using maximum entropy principle",   Advances in Knowledge Discovery and Data Mining, 6   ,2002
    View Artical

  10. H. Han and R. Elmasri,   "Learning rules for conceptual structure on the web",   J. Intell. Inf. Syst   ,Vol.22   ,2004
    View Artical

  11. M. Eirinaki and M. Vazirgiannis,   "Web mining for web personalization",   ACM Trans. Inter. Tech   ,2003
    View Artical

  12. J. Pei, J. Han, B. Mortazavi-Asl, and H. Zhu,   "Mining access patterns efficiently from web logs",   in PADKK ?00: Proceedings of the 4th Pacific-Asia    ,2000
    View Artical

  13. J. Srivastava, R. Cooley, M. Deshpande, and P.-N. Tan,   "Web usage mining: Discovery and applications of usage patterns from web data",   SIGKDD Explorations   ,Vol.1   ,2000
    View Artical

  14. J. Punin, M. Krishnamoorthy, and M. Zaki,   "Web usage mining: Languages and algorithms",   in Studies in Classification, Data Analysis,and Kn   ,2001
    View Artical

  15. P. Batista, M. ario, and J. Silva,   "Mining web access logs of an on-line newspaper   ,2002
    View Artical

  16. Sudhamathy, G.,   "Mining web logs: an automated approach",   Proceedings of the 1st Amrita ACM-W Celebration on   ,2010
    View Artical

  17. J. Hou and Y. Zhang,   "Effectively finding relevant web pages from linkage information",   IEEE Trans. Knowl. Data Eng   ,Vol.15   ,2003
    View Artical

  18. R. Iv?ncsy and I. Vajk,   "Efficient Sequential Pattern Mining Algorithms",   WSEAS Transactions on Computers   ,Vol.4   ,2005
    View Artical

  19. Paulo J. Azevedo and Al\&\#237;pio M. Jorge,   "Comparing Rule Measures for Predictive Association Rules",   Proceedings of the 18th European conference on Mac   ,2007
    View Artical

  20. Agrawal, R., Imielinski, T., Swami, A,   "Mining association rules between sets of items in large databases, in: ACM SIGMOD International Conf",   Washington DC, USA   ,1993
    View Artical

  21. Hahsler, M., Gruen, B., Hornik, K.,   "Arules: Mining Association Rules and Frequent Itemsets",   R package version 0.2-4.   ,2005
    View Artical

  22. Kannan, S., & Bhaskaran, R,   "Association rule pruning based on interestingness measures with clus-tering",   International Journal of Computer Science Issues,    ,Vol.6   ,Issue 1   ,2009
    View Artical

  23. Liqiang Geng and Howard J. Hamilton,   "Interestingness Measures for Data Mining: A Survey",   ACM Computing Surveys   ,Vol.38   ,Issue 3   ,2006
    View Artical

  24. P. Tan, V. Kumar, and J. Srivastava,   "Selecting the Right Interestingness Measure for Association Patterns",   Army High Performance Computing Research Center   ,Vol.    ,Issue    ,2002
    View Artical

  25. Liaquat Majeed Sheikh, Basit Tanveer, Syed Mustafa Ali Hamdani,   "Interesting Measures for Mining Association Rules",   In Proceedings of INMIC 2004. 8th international Mu   ,Vol.    ,2002
    View Artical

  26. Tianyi Wu, Yuguo Chen, and Jiawei Han,   "Association Mining in Large Databases: A Re-Examination of Its Measures",   In Proceedings of PKDD 11th European Conference on   ,Vol.    ,Issue    ,2007
    View Artical

  27. R. Iv?ncsy and I. Vajk,   "Time- and Memory-Efficient Frequent Itemset Discovering Algorithm for Association Rule Mining",   International Journal of Computer Applications in    ,Vol.27   ,Issue 4   ,2006
    View Artical

  28. Huang, X,   "Comparison of interestingness measures for web usage mining: An empirical study",   International Journal of Information Technology &    ,Vol.6   ,Issue 1   ,2007
    View Artical

  29. Iv?ncsy, R., & Vajk, I.,   "Frequent pattern mining in web log data.",   Journal of Applied Sciences at Budapest Tech Speci   ,Vol.3   ,Issue 1   ,2006
    View Artical

  30. Jaroszewicz , S., & Simovici, D. A,   "Pruning redundant association rules using maximum entropy principle",   Advances in Knowledge Discovery and Data Mining, 6   ,Vol.22   ,Issue 23   ,2004
    View Artical

  31. H. Han and R. Elmasri,   "Learning rules for conceptual structure on the web",   J. Intell. Inf. Syst   ,Vol.22   ,2004
    View Artical

  32. M. Eirinaki and M. Vazirgiannis,   "Web mining for web personalization",   ACM Trans. Inter. Tech   ,Vol.3   ,Issue 1   ,2003
    View Artical

  33. J. Pei, J. Han, B. Mortazavi-Asl, and H. Zhu,   "Mining access patterns efficiently from web logs",   in PADKK ?00: Proceedings of the 4th Pacific-Asia    ,Vol.    ,Issue    ,2000
    View Artical

  34. J. Srivastava, R. Cooley, M. Deshpande, and P.-N. Tan,   "Web usage mining: Discovery and applications of usage patterns from web data",   SIGKDD Explorations   ,Vol.1   ,Issue 2   ,2000
    View Artical

  35. P. Batista, M. ario, and J. Silva,   "Mining web access logs of an on-line newspaper   ,2002
    View Artical

  36. Sudhamathy, G.,   "Mining web logs: an automated approach",   Proceedings of the 1st Amrita ACM-W Celebration on   ,Vol.    ,Issue    ,2010
    View Artical

  37. J. Hou and Y. Zhang,   "Effectively finding relevant web pages from linkage information",   IEEE Trans. Knowl. Data Eng   ,Vol.15   ,Issue 4   ,2003
    View Artical

  38. R. Iv?ncsy and I. Vajk,   "Efficient Sequential Pattern Mining Algorithms",   WSEAS Transactions on Computers   ,Vol.4   ,2005
    View Artical

  39. Paulo J. Azevedo and Al\&\#237;pio M. Jorge,   "Comparing Rule Measures for Predictive Association Rules",   Proceedings of the 18th European conference on Mac   ,Vol.    ,Issue    ,2007
    View Artical

  40. Agrawal, R., Imielinski, T., Swami, A,   "Mining association rules between sets of items in large databases, in: ACM SIGMOD International Conf",   Washington DC, USA   ,Vol.22   ,Issue 2   ,1993
    View Artical

  41. Hahsler, M., Gruen, B., Hornik, K.,   "Arules: Mining Association Rules and Frequent Itemsets",   R package version 0.2-4.   ,Vol.    ,2005
    View Artical

  42. Liqiang Geng and Howard J. Hamilton,   "Interestingness Measures for Data Mining: A Survey",   ACM Computing Surveys   ,Vol.38   ,Issue 3   ,2006
    View Artical

  43. Liaquat Majeed Sheikh, Basit Tanveer, Syed Mustafa Ali Hamdani,   "Interesting Measures for Mining Association Rules",   In Proceedings of INMIC 2004. 8th international Mu   ,Vol.    ,2004
    View Artical

  44. R. Iv?ncsy and I. Vajk,   "Time- and Memory-Efficient Frequent Itemset Discovering Algorithm for Association Rule Mining",   International Journal of Computer Applications in    ,Vol.27   ,Issue 4
    View Artical

  45. Iv?ncsy, R., & Vajk, I.,   "Frequent pattern mining in web log data.",   Journal of Applied Sciences at Budapest Tech Speci   ,Vol.3   ,Issue 1   ,2008
    View Artical

  46. Jaroszewicz , S., & Simovici, D. A,   "Pruning redundant association rules using maximum entropy principle",   Advances in Knowledge Discovery and Data Mining, 6   ,Vol.    ,2002
    View Artical

  47. H. Han and R. Elmasri,   "Learning rules for conceptual structure on the web",   J. Intell. Inf. Syst   ,Vol.    ,Issue    ,2004
    View Artical

  48. M. Eirinaki and M. Vazirgiannis,   "Web mining for web personalization",   ACM Trans. Inter. Tech   ,Vol.22   ,Issue 3   ,2003
    View Artical

  49. J. Punin, M. Krishnamoorthy, and M. Zaki,   "Web usage mining: Languages and algorithms",   in Studies in Classification, Data Analysis,and Kn   ,Vol.    ,2001
    View Artical

  50. P. Batista, M. ario, and J. Silva,   "Mining web access logs of an on-line newspaper   ,2002
    View Artical

  51. Paulo J. Azevedo and Al\&\#237;pio M. Jorge,   "Comparing Rule Measures for Predictive Association Rules",   Proceedings of the 18th European conference on Mac   ,Vol.    ,2007
    View Artical

  52. Agrawal, R., Imielinski, T., Swami, A,   "Mining association rules between sets of items in large databases, in: ACM SIGMOD International Conf",   Washington DC, USA   ,Vol.1   ,Issue 5   ,1993
    View Artical

  53. Hahsler, M., Gruen, B., Hornik, K.,   "Arules: Mining Association Rules and Frequent Itemsets",   R package version 0.2-4.   ,Vol.    ,2005
    View Artical