Logic-based natural language understanding in intelligent tutoring systems.

摘要

High-precision Natural Language Understanding is needed in Geometry Tutoring to accurately determine the semantic content of students' explanations. The thesis presents a Natural Language Understanding system developed in the context of the Geometry Cognitive Tutor. The system combines unification-based syntactic processing with Description Logic based semantics to achieve the necessary accuracy level.; The thesis examines in detail the main problem faced by a natural language understanding system in the geometry tutor, that of accurately determining the semantic content of students' input. It then reviews alternative approaches used in Intelligent Tutoring Systems, and presents some difficulties these approaches have in addressing the main problem.; The thesis proceeds to describe the system architecture of our approach, as well as the compositional process of building the syntactic structure and the semantic interpretation of students' explanations. The syntactic and semantic processing of natural language are described in detail, as well as solutions for specific natural language understanding problems, like metonymy resolution and reference resolution.; The thesis also discusses a number of problems occurring in determining semantic equivalence of natural language input and shows how our approach deals with them. The classification performance of the adopted solution is evaluated on data collected during a recent classroom study and is compared to a Naive Bayes approach.; The generality of our solution is demonstrated in a practical experiment of porting the approach to a new semantic domain, Algebra. The thesis discusses the changes needed in the new implementation, the time effort required, and presents the classification performance in the new domain.; Finally, the thesis provides a high level Description Logic view of the presented approach to semantic representation and inference, and talks about the possibility to implement it in other logic systems.