Abstract:In this paper, the concepts of weighted support and preference are proposed to reflect user interests accurately. Linguistic evaluations on a web page given by experts are characterized as fuzzy linguistic variables. These fuzzy linguistic variables can be transformed as an importance weight of a web page by fuzzy simulation. To avoid loss of important user browsing information, FLAAT (frequent link and access tree) is built to save all user browsing information. Then user preferred browsing patterns can be mined from the FLAAT. In addition, time duration on web page is another important factor reflecting user interests and preference, which is also denoted by a corresponding fuzzy linguistic variable. Experimental results show the gained user preferred patterns with fuzzy time duration reflect user interests and preference more accurately.
[1] Chen M S, Park J S, Yu P S. Efficient Data Mining for Path Traversal Patterns. IEEE Trans on Knowledge and Data Engineering, 1998, 10(2): 209221 [2] Hong T, Chiang M J, Wang S L. Mining Weighted Browsing Patterns with Linguistic Minimum Supports // Proc of the IEEE International Conference on Systems, Man and Cybernetics. Yasmine Hammamet, Tunisia, 2002, Ⅳ: 635639 [3] Liu Baoding, Liu Y K. Expected Value of Fuzzy Variable and Fuzzy Expected Value Models.IEEE Trans on Fuzzy Systems, 2002, 10(4): 445450 [4] Pal S K, Talwar V, Mitra P. Web Mining in Soft Computing Framework: Relevance, State of the Art and Future Directions. IEEE Trans on Neural Networks, 2002, 13(5): 11631177 [5] Jin Yang, Zuo Wanli. An Ordered Concept Lattice and Incremental Mining of User Traversal Patterns on the WWW. Journal of Computer Research and Development, 2003, 40(5): 675683 (in Chinese) (金 阳,左万利.有序概念格与WWW用户访问模式的增量挖掘.计算机研究与发展, 2003, 40(5): 675683) [6] Zadeh L. Fuzzy Sets. Information and Control, 1965, 8(3): 338353 [7] Lo W S, Hong T P, Wang S L. A TopDown Fuzzy CrossLevel WebMining Approach // Proc of the IEEE International Conference on Systems, Man and Cybernetics. Washington, USA, 2003, Ⅲ: 26842689 [8] Xing D, Shen J. Efficient Data Mining for Web Navigation Patterns. Information and Software Technology, 2004, 46(1): 5563