Abstract
The End-User Access to Multiple Sources, the EAMS system integrates document collections in the internet (intranet) and relational databases by an ontology. The ontology relates the document with the database world and generates the items in the user interface. In both worlds, machine learning is applied. In the document world, a learning search engine adapts to user behavior by analysing the click-through- data. In the database world, knowledge discovery in databases (KDD) bridges the gap between the fine granularity of relational databases and the coarse granularity of the ontology. KDD extracts knowledge from data and therefore allows the knowledge management system to make good use of already existing company data. The EAMS system has been applied to customer relationship management in the insurance domain. Questions to be answered by the system concern customer acquisition (e.g., direct marketing), customer up and cross selling (e.g., which products sell well together), and customer retention (here: which customers are likely to leave the insurance company or ask for a return of a capital life insurance). Documents about other insurance companies and demographic data published in the internet contribute to the answers as do the results of data analysis of the company’s contracts.
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Morik, K., Hüppej, C., Unterstein, K. (2002). End-User Access to Multiple Sources - Incorporating Knowledge Discovery into Knowledge Management. In: Karagiannis, D., Reimer, U. (eds) Practical Aspects of Knowledge Management. PAKM 2002. Lecture Notes in Computer Science(), vol 2569. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36277-0_22
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