A machine learning workbench in a DOOD framework
In this paper we present a machine learning workbench, which we have developed by making use of deductive object-oriented database (DOOD) technology. It provides a comfortable environment for performing a large variety of machine learning tasks. By deriving full benefit of the available powerful logic and object-oriented programming language, we have implemented an easily extendable representative collection of machine learning algorithms. As realistic case study for the feasibility of the workbench we applied it to the automatic acquisition of linguistic knowledge within a natural language database interface.
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