Abstract
A brief review of the current research on the development of the VINLEN multitask inductive database and decision support system is presented. The aim of this research is to integrate a wide range of knowledge generation operators in one system that given input data and relevant domain knowledge generates new knowledge according to the user’s goal. The central VINLEN operator is natural induction that generates hypotheses from data in the form of attributional rules that resemble natural language expressions, and are easy to understand and interpret. This operator is illustrated by an application to discovering relationships between lifestyles and diseases of men age 50-65 in a large database created by the American Medical Association. The conclusion outlines plans for future research.
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Kaufman, K.A., Michalski, R.S., Pietrzykowski, J., Wojtusiak, J. (2007). An Integrated Multi-task Inductive Database VINLEN: Initial Implementation and Early Results. In: Džeroski, S., Struyf, J. (eds) Knowledge Discovery in Inductive Databases. KDID 2006. Lecture Notes in Computer Science, vol 4747. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75549-4_8
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DOI: https://doi.org/10.1007/978-3-540-75549-4_8
Publisher Name: Springer, Berlin, Heidelberg
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