incremental compilation of knowledge documents for markup-based closed-world authoring
Text-based authoring using knowledge markups is an increasingly popular editing paradigm in manual knowledge acquisition. Closed world authoring environments support the user to form a coherent knowledge base by checking the referenced objects against a set of declared domain objects. In this scenario, the task of efficient translation (compilation) of the text sources is non-trivial. Additionally, in real-world applications frequent small changes are performed on the source documents and instant feedback to the author is crucial. Therefore, a scalable compilation into the target knowledge representations is necessary. In this paper, we introduce a general algorithm for the incremental compilation of knowledge documents, that analyzes the current document modifications and performs minimal updates on the knowledge base. We provide a formal proof of the correctness of the algorithm and show the effectiveness of the approach in several case studies, using various kinds of knowledge representations and markups.
knowledge markup knowledge acquisition source compilation