Abstract
Combining the paths similarity and the pages content similarity, a novel clustering algorithm is presented. The actions character of users is revealed more exactly by clustering. The data scale is reduced by a long way during clustering. Based on the clusters, the user navigation patterns are generated by mining the Web log. The experiment result shows that the user navigation interest conversion patterns mined from Web log are typical and intuitionistic.
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Feng, G., Ma, GS., Hu, J. (2006). Web Navigation Patterns Mining Based on Clustering of Paths and Pages Content. In: Shen, H.T., Li, J., Li, M., Ni, J., Wang, W. (eds) Advanced Web and Network Technologies, and Applications. APWeb 2006. Lecture Notes in Computer Science, vol 3842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11610496_118
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DOI: https://doi.org/10.1007/11610496_118
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31158-4
Online ISBN: 978-3-540-32435-5
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