FEATURE-TAK - Framework for Extraction, Analysis, and Transformation of Unstructured Textual Aircraft Knowledge
| Autor: | Pascal Reuss, Frieder Henning, Cedric Juckenack, Rotem Stram, Klaus-Dieter Althoff, Daniel Fischer, Wolfram Henkel |
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| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Vocabulary Association rule learning business.industry Computer science media_common.quotation_subject Keyword extraction Unstructured data 02 engineering and technology computer.software_genre Domain (software engineering) 03 medical and health sciences 030104 developmental biology Knowledge extraction 020204 information systems Similarity (psychology) 0202 electrical engineering electronic engineering information engineering Feature (machine learning) Artificial intelligence business computer Natural language processing media_common |
| Zdroj: | Case-Based Reasoning Research and Development ISBN: 9783319470955 ICCBR |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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