This paper describes a novel framework for interactive question-answering (Q/A) based on predictive questioning. Generated off-line from topic representations of complex scenarios, predictive questions represent requests for information that capture the most salient (and diverse) aspects of a topic. We present experimental results from large user studies (featuring a fully-implemented interactive Q/A system named FERRET) that demonstrates that surprising performance is achieved by integrating predictive questions into the context of a Q/A dialogue.
Recently, an architecture for interactive question answering has been proposed based on a notion of predictive questioning REF .
Experiments With Interactive Question-Answering
Annual Meeting Of The Association For Computational Linguistics
Computer Science