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|Title:||From knowledge discovery to implementation: A business intelligence approach using neural network rule extraction and decision tables||Authors:||Mues, C.
|Issue Date:||2005||Citation:||Mues, C.,Baesens, B.,Setiono, R.,Vanthienen, J. (2005). From knowledge discovery to implementation: A business intelligence approach using neural network rule extraction and decision tables. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3782 LNAI : 483-495. ScholarBank@NUS Repository.||Abstract:||The advent of knowledge discovery in data (KDD) technology has created new opportunities to analyze huge amounts of data. However, in order for this knowledge to be deployed, it first needs to be validated by the end-users and then implemented and integrated into the existing business and decision support environment. In this paper, we propose a framework for the development of business intelligence (BI) systems which centers on the use of neural network rule extraction and decision tables. Two different types of neural network rule extraction algorithms, viz. Neurolinear and Neurorule, are compared, and subsequent implementation strategies based on decision tables are discussed. © Springer-Verlag Berlin Heidelberg 2005.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/42848||ISBN:||3540304657||ISSN:||03029743|
|Appears in Collections:||Staff Publications|
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