FEATURE-TAK - Framework for Extraction, Analysis, and Transformation of Unstructured Textual Aircraft Knowledge

Pascal Reuss, Rotem Stram, Cedric Juckenack, Klaus-Dieter Althoff, Wolfram Henkel, Daniel Fischer, Frieder Henning

In: Ashok Goal, Belen Diaz-Agudo, Thomas Roth-Berghofer (Hrsg.). Case-based Reasoning in Research and Development. International Conference on Case-Based Reasoning (ICCBR-2016) 24th October 31-November 2 Atlanta Georgia United States LNCS Springer Berlin Heidelberg 2016.


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 case-based reasoning (CBR) systems, methods and algorithms from natural language processing and CBR are required. Our framework integrates diff erent 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 diff erent 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.


ICCBR2016_paper_37_final.pdf (pdf, 712 KB)

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence