Detecting Opinionated Sentences by Extracting Context Information

Xinfan Meng, Houfeng Wang
2008 NTCIR Conference on Evaluation of Information Access Technologies  
In this paper, we briefly describe several experimental methods to solve MOAT at NTCIR-7. In the subtask of opinionated sentence detection, two methods aiming to extract the context information of each sentence are proposed. Maximum Entropy model is used to predict the polarity class. A rule-based pattern matching scheme is devised to find topic-relevant sentence. For the subtask of detecting holders and targets, the CRF model is adopted.
dblp:conf/ntcir/MengW08 fatcat:xgktdbxdbjc2xndyfnvgkzp56q