Reading to Learn: An Investigation into Language Understanding

Machine Reading

Volume

Papers from the 2007 AAAI Spring Symposium

Contents

One of the most important methods by which human beings learn is by reading. While in its full generality, the reading task is still too difficult a capability to be implemented in a computer, significant (if partial) approaches to the task are now feasible. Our goal in this project was to study issues and develop solutions for this task by working with a reduced version of the problem, namely working with text written in a simplified version of English (a Controlled Language) rather than full natural language. Our experience and results reveal that even this reduced version of the task is still challenging, and we have uncovered several major insights into this challenge. We describe our work and analysis, present a synthesis and evaluation of our work, and make several recommendations for future work in this area. Our conclusion is that ultimately, to bridge the "knowledge gap", a pipelined approach is inappropriate, and that to address the knowledge requirements for good language understanding an iterative (bootstrapped) approach is the most promising way forward.