Business Rule Learning with Interactive Selection of Association Rules

Provided by: University of Economics, Prague
Topic: Data Management
Format: PDF
Today, there is an increasing demand for Decision Support Systems (DSS). The penetration of DSS solutions to many domains is stifled by the fact that building a DSS requires a significant amount of time from users, who need to be not only domain experts, but also skilled knowledge engineers. This paper presents the implementation of a classification system based on learning of association rules in conjunction with Drools rule engine. The rules are interactively discovered with a web-based data mining system EasyMiner.eu. The rules are approved and edited by the domain expert before they are deployed for classification.

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