Paper: A Probabilistic Framework for Answer Selection in Question Answering

ACL ID N07-1066
Title A Probabilistic Framework for Answer Selection in Question Answering
Venue Human Language Technologies
Session Main Conference
Year 2007
Authors

This paper describes a probabilistic an- swer selection framework for question an- swering. In contrast with previous work using individual resources such as ontolo- gies and the Web to validate answer can- didates, our work focuses on developing a unified framework that not only uses multiple resources for validating answer candidates, but also considers evidence of similarity among answer candidates in or- der to boost the ranking of the correct an- swer. This framework has been used to se- lect answers from candidates generated by four different answer extraction methods. An extensive set of empirical results based on TREC factoid questions demonstrates the effectiveness of the unified framework.