Abstract

This paper describes a framework for semi-automatic knowledge extraction for case-based diagnosis in the aircraft domain. The available data on historical problems and their solutions contain structured and unstructured data. To transform these data into knowledge for CBR systems, methods and algorithms from natural language processing and case-based reasoning are required. Our framework integrates different algorithms and methods to transform the available data into knowledge for vocabulary, similarity measures, and cases. We describe the idea of the framework as well as the different tasks for knowledge analysis, extraction, and transformation. In addition, we give an overview of the current implementation, our evaluation in the application context, and future work.

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