Abstract
With the emergence of the World Wide Web, Web sites have become a key communication channel for organizations. In this context, analyzing and improving Web communication is essential to better satisfy the objectives of the target audience. Web communication analysis is traditionnally performed by Web analytics software, which produce long lists of audience metrics. These metrics contain little semantics and are too detailed to be exploited by organization managers and chief editors, who need summarized and conceptual information to take decisions. Our solution to obtain such conceptual metrics is to analyze the content of the Web pages output by the Web server. In this paper, we first present a list of methods that we conceived to mine the output Web pages. Then, we explain how term weights in these pages can be used as audience metrics, and how they can be aggregated using OLAP tools to obtain concept-based metrics. Finally, we present the concept-based metrics that we obtained with our prototype WASA and SQL Server OLAP tools.
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Norguet, JP., Zimányi, E., Steinberger, R. (2006). Improving Web Sites with Web Usage Mining, Web Content Mining, and Semantic Analysis. In: Wiedermann, J., Tel, G., Pokorný, J., Bieliková, M., Štuller, J. (eds) SOFSEM 2006: Theory and Practice of Computer Science. SOFSEM 2006. Lecture Notes in Computer Science, vol 3831. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11611257_41
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DOI: https://doi.org/10.1007/11611257_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31198-0
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