A Cognitive-Related Entity and Relation Extraction Model for Online Tutoring Systems

摘要

The significance of knowledge management in Intelligent tutoring system is that it can help learners better understand, manage and transfer knowledge. However, the knowledge management modules in most intelligent tutoring systems still based on structured domain knowledge. Although many studies have focused on constructing the unstructured concepts of the knowledge, concepts' exacting is still an open problem. This paper proposes a basic model to extract and construct the unstructured knowledge from online learning resources called Cognitive-related entity and relation extraction model (CERE) based on the Semantic Linked Network (SLN) technology. The experiment shows that in the field of concept knowledge, this model can effectively extract the conceptual entities with cognitive value and the predefined semantic relations, and these entities and semantic relations are closely related to learners' cognitive motivations. The automatic implementation of the unstructured concepts' extraction and relation building also suggests that the reducing of the dependences on domain experts is possible.