Abstract
Web-based commerce systems fail to achieve many of the features that enable small businesses to develop a friendly human relationship with customers. Although many enterprises have worried about user identification to solve the problem, the solution goes far beyond trying to find out what navigator’s behavior looks like. Many approaches have recently been proposed to enrich the data in web logs with semantics related to the business so that web mining algorithms can later be applied to discover patterns and trends. In this paper we present an innovative method of log enrichment as several goals and viewpoints of the organization owning the site are taken into account. By later applying discriminant analysis to the information enriched this way, it is possible to identify the relevant factors that contribute most to the success of a session for each viewpoint under consideration. The method also helps to estimate ongoing session value in terms of how the company’s objectives and expectations are being achieved.
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Menasalvas, E., Millán, S., Pérez, M.S., Hochsztain, E., Tasistro, A. (2004). An Approach to Estimate the Value of User Sessions Using Multiple Viewpoints and Goals. In: Berendt, B., Hotho, A., Mladenič, D., van Someren, M., Spiliopoulou, M., Stumme, G. (eds) Web Mining: From Web to Semantic Web. EWMF 2003. Lecture Notes in Computer Science(), vol 3209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30123-3_10
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DOI: https://doi.org/10.1007/978-3-540-30123-3_10
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