Abstract
The problem of knowledge extraction from the data left by web users during their interactions is a very attractive research task. The extracted knowledge can be used for different goals such as service personalization, site structure simplification, web server performance improvement or even for studying the human behavior. The objective of this paper is to present a system, called ELM (Event Logger Manager), able to register and analyze data from different applications. The registered data can be specified in an experiment. Currently ELM system provides several knowledge mining algorithms, i.e., apriori, ID3, C4.5 but easily other mining algorithms can be added.
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Bluemke, I., Orlewicz, A. (2009). System for Knowledge Mining in Data from Interactions between User and Application. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_10
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DOI: https://doi.org/10.1007/978-3-642-00563-3_10
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