Sciweavers

Share
ICML
2005
IEEE

Learning strategies for story comprehension: a reinforcement learning approach

10 years 3 months ago
Learning strategies for story comprehension: a reinforcement learning approach
This paper describes the use of machine learning to improve the performance of natural language question answering systems. We present a model for improving story comprehension through inductive generalization and reinforcement learning, based on classified examples. In the process, the model selects the most relevant and useful pieces of lexical information to be used by the inference procedure. We compare our approach to three prior non-learning systems, and evaluate the conditions under which learning is effective. We demonstrate that a learning-based approach can improve upon "matching and extraction"only techniques.
Eugene Grois, David C. Wilkins
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2005
Where ICML
Authors Eugene Grois, David C. Wilkins
Comments (0)
books