Abstract
Extracting patterns from Web usage data helps to facilitate better Web personalization and Web structure readjustment. There are a number of different approaches proposed for Web Usage Mining, such as Markov models and their variations, or models based on pattern recognition techniques such as sequence mining. This paper describes a new framework, which combines clustering of users’ sessions together with a novel algorithm, called PathSearch-BF, in order to construct smart access paths that will be presented to the Web users for assisting them during their navigation in the Web sites. Through experimental evaluation on well-known datasets, we show that the proposed methodology can achieve valuable results.
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Kirmemis Alkan, O., Karagoz, P. (2013). Assisting Web Site Navigation through Web Usage Patterns. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_17
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DOI: https://doi.org/10.1007/978-3-642-38577-3_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38576-6
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