Paper: A Joint Information Model for N-Best Ranking

ACL ID C08-1086
Title A Joint Information Model for N-Best Ranking
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008
Authors

In this paper, we present a method for modeling joint information when gene- rating n-best lists. We apply the method to a novel task of characterizing the simi- larity of a group of terms where only a small set of many possible semantic properties may be displayed to a user. We demonstrate that considering the re- sults jointly, by accounting for the infor- mation overlap between results, generates better n-best lists than considering them independently. We propose an informa- tion theoretic objective function for mod- eling the joint information in an n-best list and show empirical evidence that humans prefer the result sets produced by our joint model. Our results show with 95% confidence that the n-best lists gen- erated by our joint ranking model are significantly differe...