Abstract
Web log mining is used to extract user access pattern. An algorithm is proposed in this paper to resolve the problem of bad explanation for page sequence of web log mining. The algorithm firstly transforms user visited page sequence into maximal forward sequence, and then uses HowNet based semantic similar algorithm to describe user interest in visit sequence and explains the interest movement with certain semantic words. The algorithm will help web sites provide personalization pages.
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References
R. Agrawal and R. Srikant, Mining Sequential Patterns, in Proc. of the 11th International Conference on Data Engineering (IEEE Computer Society Press: Washington DC, USA, 1995), pp.3–14.
M.S. Chen, J.S. Park, and P.S. Yu, Efficient data mining for path traversal patterns, IEEE Trans Knowledge Data Engn. Volume 10, Number 2, pp.209–221, (1998).
X. Ma, H. Ling, Y. Liu, and Y. Jiang, An Ant Colony Approach for Discovery of Users Interest Navigation Paths, Chinese Journal of Management Science. Volume 14, Number 3, pp.56–59, (2006).
B. He, W. Yang, J. Zhang, and Y. Wang, Intelligent information recommendation algorithm based on user model clustering, Computer Engineering and Design. Volume 27, Number 13, pp.2360–2361, (2006).
Z. Dong and Q. Dong, HowNt (March 6, 2004). http://www.keenage.com/zhiwang/c_zhiwang.html
S. Li, J. Zhang, X. Huang, and S. Bai, Semantic Computation in Chinese Question-Answering System, Journal of Computer Science and Technology. Volume 17, Number 6, pp.933–939, (2002).
Q. Liu and S. Li, Word Similarity Computing Based on HowNet, Computational Linguistics and Chinese Language Processing. Volume 7, pp.59–76, (2002).
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© 2008 International Federation for Information Processing
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Li, C., Qi, J., Shu, H. (2008). A HowNet Based Web Log Mining Algorithm. In: Xu, L.D., Tjoa, A.M., Chaudhry, S.S. (eds) Research and Practical Issues of Enterprise Information Systems II. IFIP International Federation for Information Processing, vol 255. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-76312-5_15
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DOI: https://doi.org/10.1007/978-0-387-76312-5_15
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-76311-8
Online ISBN: 978-0-387-76312-5
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