Abstract
This paper proposes a new algorithm, called TAM WAP(the shorthand forTop down Algorithm for Mining Web AccessPatterns), to mine interesting WAP from Web logs. TAM WAP searches the P tree database in the top down manner to mine WAP. By selectively building intermediate data according to the features of current area to be mined, it can avoid stubbornly building intermediate data for each step of mining process. The experiments for both real data and artificial data show that our algorithm outperforms conventional methods.
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Jian-Kui, G. et al. (2005). A Top Down Algorithm for Mining Web Access Patterns from Web Logs. In: Ho, T.B., Cheung, D., Liu, H. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2005. Lecture Notes in Computer Science(), vol 3518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11430919_99
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DOI: https://doi.org/10.1007/11430919_99
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26076-9
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