Ontology, used to systematically model the domain knowledge, fa-cilitates not only computation but also cognitive processing of human brain. Whereas, interpretation process involves similar brain activities, an ontology-based training method is proposed for topic-based interpretation training (TBIT) to meet its two major teaching objectives: Both subject knowledge and LSP (Lan-guage for Special Purpose) knowledge are to be acquired by learners. Ontology can help interpreters to clarify unfamiliar concepts, acquire knowledge and trans-form it into long term memory (LTM). An ontology-based training can improve interprter's information processing ability, anticipation ability, and short term memory capacity so that a high efficiency of prior knowledge operation can be re-alized and better quality of rendering can be produced. © 2013 Springer-Verlag.
CITATION STYLE
Feng, M. (2013). An ontology-based approach for topic-based interpretation training. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7717 LNAI, pp. 818–828). https://doi.org/10.1007/978-3-642-36337-5_83
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