Paper: Extracting Opinion Targets in a Single and Cross-Domain Setting with Conditional Random Fields

ACL ID D10-1101
Title Extracting Opinion Targets in a Single and Cross-Domain Setting with Conditional Random Fields
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010
Authors

In this paper, we focus on the opinion tar- get extraction as part of the opinion min- ing task. We model the problem as an in- formation extraction task, which we address based on Conditional Random Fields (CRF). As a baseline we employ the supervised al- gorithm by Zhuang et al. (2006), which rep- resents the state-of-the-art on the employed data. We evaluate the algorithms comprehen- sively on datasets from four different domains annotated with individual opinion target in- stances 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 perfor- mance by 0.077, 0.126, 0.071 and 0.178 re- garding F-Measure in the single-domain ex- tractio...