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Mining Web Access Patterns using Root-set of Suffix Trees
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 94 - Number 9 |
| Year of Publication: 2014 |
| Authors: Manira Akhter, Ashin Ara Bithi, Abu Ahmed Ferdaus |
10.5120/16372-5818
|
Manira Akhter, Ashin Ara Bithi, Abu Ahmed Ferdaus . Mining Web Access Patterns using Root-set of Suffix Trees. International Journal of Computer Applications. 94, 9 ( May 2014), 23-29. DOI=10.5120/16372-5818
Abstract
With the rapidly growing uses of World Wide Web for various important and sensitive purposes it becomes a sensible necessity to find out the interesting web access patterns from the web access sequences tracked by users frequently. Web access sequential patterns can be used to achieve business intelligence for e-commerce sites and also can be used to analyze system performance. This paper proposes a more efficient web mining algorithm which mines all the sequential patterns from the web access sequences and totally eliminates the concept of linking between nodes. The algorithm uses the aggregate tree structure for mining and then mines from the tree using RST (Root-set of Suffix Trees) for same prefix items. The algorithm finds the frequent sequential patterns by recursively traversing the tree from root-nodes to child-nodes for the length-1 frequent items. The proposed approach doesn't need to generate any projected tree; it needs only the root-set for each prefix that got in previous step. Experimental results show huge performance gain over the FOF and WAP-tree mining techniques by considerably reducing the mining time.
References
- R. Srikant and R. Agrawal, "Mining sequential patterns: Generalizations and performance improvements," in EDBT, ser. Lecture Notes in Computer Science, P. M. G. Apers, M. Bouzeghoub, and G. Gardarin, Eds. , vol. 1057. Springer, 1996, pp. 3-17. [Online]. Available: http://dx. doi. org/10. 1007/BFb0014140.
- J. Pei, J. Han, B. Mortazavi-Asl, and H. Zhu, "Mining access patterns efficiently from web logs," in PAKDD, ser. Lecture Notes in Computer Science, T. Terano, H. Liu, and A. L. P. Chen, Eds. , vol. 1805. Springer, 2000, pp. 396-407. [Online]. Available: http://dx. doi. org/10. 1007/3-540-45571-X 47
- C. I. Ezeife and Y. Lu, "Mining web log sequential patterns with position coded pre-order linked WAP-tree," Data Min. Knowl. Discov, vol. 10, no. 1, pp. 5-38, 2005. [Online]. Available: http://dx. doi. org/10. 1007/s10618-005-0248-3
- P. Tang, M. P. Turkia, and K. A. Gallivan, "Mining web access patterns with first-occurrence linked WAP-trees," in SEDE, H. Al-Mubaid and M. Garbey, Eds. ISCA, 2007, pp. 247-252.
- E. A. Peterson and P. Tang, "Mining frequent sequential patterns with first-occurrence forests," in ACM Southeast Regional Conference. ACM, 2008, pp. 34-39. [Online]. Available: http://doi. acm. org/10. 1145/1593105. 1593115
- J. Han, J. Pei, and Y. Yin, "Mining frequent patterns without candidate generation," in SIGMOD Conference, W. Chen, J. F. Naughton, and P. A. Bernstein, Eds. ACM, 2000, pp. 1-12. [Online]. Available: http://doi. acm. org/10. 1145/342009. 335372
- M. Spiliopoulou and L. Faulstich, "WUM - A tool for WWW ulitization analysis," in WebDB, ser. Lecture Notes in Computer Science, P. Atzeni, A. O. Mendelzon, and G. Mecca, Eds. , vol. 1590. Springer, 1998, pp. 184-103. [Online]. Available:http://dx. doi. org/10. 1007/10704656 12
- Z. Zheng, R. Kohavi, and L. Mason, "Real world performance of association rule algorithms," in KDD, 2001, pp. 401-406. [Online]. Available: http://portal. acm. org/citation. cfm?id=502512. 502572
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