Learning foci for Question Answering over Topic Maps

The paper on Question Answering I have cowritten with Rani Pinchuk and Tiphaine Dalmas for ACL-IJCNLP'09.


This paper introduces the concepts of asking point and
expected answer type as variations of the question focus.
They are of particular importance for QA over semi-structured data, as
represented by Topic Maps, OWL or custom XML formats. We describe an approach
to the identification of the question focus from questions asked to a
Question Answering system over Topic Maps by extracting the asking
and falling back to the expected answer type when necessary.
We use known machine learning techniques for expected answer type
extraction and we implement a novel approach to the asking point
extraction. We also provide a mathematical model to predict the performance
of the system.

See the paper in the attachment.