Abstract
Web data or data originated on the Web contain information and knowledge which allows to improve web site efficiency and effectiveness to attract and retain visitors.
However, web data have many irrelevant data inside. Consequently, it is necessary to preprocess them to model and understand the web user browsing behavior inside them. Further, due to frequent changes in the visitor’s behavior, as well as in the web site itself, the discovered knowledge may become obsolete in a short period of time.
In this paper, we introduce a platform which extracts, preprocesses and stores web data to enabling the utilization of web mining techniques. In other words, there is an Information Repository (IR) which stores preprocessed web data and it facilitates the patterns extraction. Likewise, there is a Knowledge Base (KB) for storing the discovered patterns which have been validated by a domain expert.
The proposed structure was tested using a real web site to prove the effectiveness of our approach.
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Rebolledo, L.V., Velásquez, J.D. (2009). A Platform for Extracting and Storing Web Data. In: Velásquez, J.D., Ríos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5712. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04592-9_104
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DOI: https://doi.org/10.1007/978-3-642-04592-9_104
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04591-2
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