Paper: Multiple Aspect Ranking Using the Good Grief Algorithm

ACL ID N07-1038
Title Multiple Aspect Ranking Using the Good Grief Algorithm
Venue Human Language Technologies
Session Main Conference
Year 2007
Authors

We address the problem of analyzing mul- tiple related opinions in a text. For in- stance, in a restaurant review such opin- ions may include food, ambience and ser- vice. We formulate this task as a multiple aspect ranking problem, where the goal is to produce a set of numerical scores, one for each aspect. We present an algorithm that jointly learns ranking models for in- dividual aspects by modeling the depen- dencies between assigned ranks. This al- gorithm guides the prediction of individ- ual rankers by analyzing meta-relations between opinions, such as agreement and contrast. We prove that our agreement- based joint model is more expressive than individual ranking models. Our empirical results further con rm the strength of the model: the algorithm provides signi cant improvement ov...