Paper: Optimizing Question Answering Accuracy by Maximizing Log-Likelihood

ACL ID P10-2044
Title Optimizing Question Answering Accuracy by Maximizing Log-Likelihood
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2010
Authors

In this paper we demonstrate that there is a strong correlation between the Ques- tion Answering (QA) accuracy and the log-likelihood of the answer typing com- ponent of our statistical QA model. We exploit this observation in a clustering al- gorithm 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 ac- curacy using the resulting clusters than by using manually derived clusters.