A Fuzzy Data Warehouse Approach for Web Analytics

Authors:
Daniel Fasel;Darius Zumstein
Affiliations:
Information Systems Research Group, Department of Informatics, University of Fribourg, Fribourg, Switzerland 1700;Information Systems Research Group, Department of Informatics, University of Fribourg, Fribourg, Switzerland 1700
Venue:
WSKS '09 Proceedings of the 2nd World Summit on the Knowledge Society: Visioning and Engineering the Knowledge Society. A Web Science Perspective
Year:
2009

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Abstract

The analysis of web data and metrics became an important task of e-business to control and optimize the website, its usage and online marketing. Firstly, this paper shows the use of web analytics, different web metrics of Google Analytics and other Key Performance Indicators (KPIs) of e-business. Secondly, this paper proposes a fuzzy data warehouse approach to improve web analytics. The fuzzy logic approach allows a more precise classification and segmentation of web metrics and the use of linguistic variables and terms. In addition, the fuzzy data warehouse model discusses the creation of fuzzy multidimensional classification spaces using dicing operations and shows the potential of fuzzy slices, dices and aggregations compared to sharp ones. The added value of web analytics, web usage mining and the fuzzy logic approach for the information and knowledge society are also discussed.