Abstract

Written instructions are a common way of teaching people how to accomplish tasks on the web. However, studies have shown that written instructions are diffificult to follow, even for experienced users. A system that understands human-written instructions could guide users through the process of following the directions, improving completion rates and enhancing the user experience. While general natural language understanding is extremely diffifi- cult, we believe that in the limited domain of howto instructions it should be possible to understand enough to provide guided help in a mixed-initiative environment. Based on a qualitative analysis of instructions gathered for 43 web-based tasks, we have formalized the problem of understanding and interpreting how-to instructions. We compare three different approaches to interpreting instructions: a keyword-based interpreter, a grammar-based interpreter, and an interpreter based on machine learning and information extraction. Our empirical results demonstrate the feasibility of automated how-to instruction understanding