Abstract
Each user accesses a Website with certain interest. The interest is associated with his navigation patterns. The interest navigation patterns represent different interest of the users. In this paper, hybrid Markov model is proposed for interest navigation pattern discovery. The novel model is better in prediction overlay rate and prediction correct rate than traditional Markov models. User group interest is also defined in this paper. The probability of user group interest navigation from one page to another is computed by navigation path characteristics and time characteristics. Compared with the previous ones, the results of the experiment show that the performance is improved efficiently by the hybrid Markov model.
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Yu, Y., Lin, H., Yu, Y., Chen, C. (2006). Mining Interest Navigation Patterns Based on Hybrid Markov Model. In: Larsen, H.L., Pasi, G., Ortiz-Arroyo, D., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2006. Lecture Notes in Computer Science(), vol 4027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11766254_39
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DOI: https://doi.org/10.1007/11766254_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34638-8
Online ISBN: 978-3-540-34639-5
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