Abstract: This paper describes the first stage of question analysis in Question Answering over Topic Maps. It introduces the concepts of asking point and expected answer type as variations of the question focus. We identify the question focus in questions asked to a Question Answering system over Topic Maps. We use known machine learning techniques for expected answer type extraction and implement a novel approach to the asking point extraction. We also provide a mathematical model to predict the performance of the system.
This full paper is part oft the session Query and Update at the TMRA 2009 conference.
