The paper “Extracting Opinion Targets in a Single- and Cross-Domain Setting with Conditional Random Fields” by Niklas Jakob and Iryna Gurevych has been accepted at EMNLP 2010 (Conference on Empirical Methods in Natural Language Processing).

Abstract:

In this paper, we focus on the opinion target extraction as part of the opinion mining task. We model the problem as an information extraction task, which we address based on Conditional Random Fields (CRF). As a baseline we employ an algorithm, which represents the state-of-the-art on the employed data. We evaluate the algorithms comprehensively on datasets from four different domains annotated with individual opinion target instances on a sentence level. Furthermore, we investigate the performance of our CRF-based approach and the baseline in a single- and cross-domain opinion target extraction setting. Our CRF-based approach improves the performance by 0.077, 0.126, 0.071 and 0.178 regarding F-Measure in the single-domain extraction in the four domains. In the cross-domain setting our approach improves the performance by 0.409, 0.242, 0.294 and 0.343 regarding F-Measure.

https://www.ukp.tu-darmstadt.de/publications/details/?no_cache=1&pub_id=TUD-CS-2010-0171