Using natural language to represent knowledge in an intelligent tutoring system

Authors:
Sung-Young Jung
Affiliations:
University of Pittsburgh, Pittsburgh, PA, USA
Venue:
Proceedings of the fifth international conference on Knowledge capture
Year:
2009

Citing 4
Cited 0

Learner: a system for acquiring commonsense knowledge by analogy

Proceedings of the 2nd international conference on Knowledge capture
Modeling semantic containment and exclusion in natural language inference

COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Solving mechanics problems using meta-level inference

IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 2
Representations of knowledge in a program for solving physics problems

IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 1

Quantified Score

Hi-index	0.00

Visualization

Abstract

Developing intelligent tutoring systems (ITS) for a target domain includes authoring tasks requiring long time and efforts. Letting authors use natural language to represent various kinds of knowledge is a way that any authors can add and update knowledge easily. An authoring system acquiring knowledge represented in natural language for an equation-based tutor (Pyrenees) is presented in this paper. This authoring system was designed to acquire not only problem statements, but also commonsense and domain knowledge in natural language from authors.