Optimizing Question Answering Accuracy by Maximizing Log-Likelihood

In this paper we demonstrate that there is a strong correlation between the Question Answering (QA) accuracy and the log-likelihood of the answer typing component of our statistical QA model. We exploit this observation in a clustering algorithm which optimizes QA accuracy by maximizing the log-likelihood of a set of question-and-answer pairs. Experimental results show that we achieve better QA accuracy using the resulting clusters than by using manually derived clusters.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Matthias H. Heie, Edward W. D. Whittaker, Sadaoki Furui
• Keywords: ACL 2010, Computational Linguistics, QA Accuracy, Question-and-answer Pairs, Statistical Qa Model