Semi-automatic knowledge extraction from semi-structured and unstructured data within the OMAHA project

Abstract

This paper describes a workflow for semi-automatic knowledge extraction for case-based diagnosis in the aircraft domain. There are different types of data sources: structured, semi-structured and unstructured source. Because of the high number of data sources available and necessary, a semi-automatic extraction and transformation of the knowledge is required to support the knowledge engineers. This support shall be performed by a part of our multi-agent system for aircraft diagnosis. First we describe our multi-agent system to show the context of the knowledge extraction. Then we describe our idea of the workflow with its single tasks and substeps. At last the current implementation, and evaluation of our system is described.