Combining dependency parsing with shallow semantic analysis for Chinese opinion-element relation identification

Sentiment analysis is an important subtask for Opinion Mining, among which how to identify the opinion-element relation between a topic and a sentiment modifying it is an essential step. This paper presents a novel method to identify the opinion-element relation based on the dependency parsing analysis as well as shallow semantic analysis, using an ontology dictionary and a collocation database to take full consideration of the semantic behind the topic and sentiment. The experiment result shows that compared to the baseline our method can further improve both the recall and precision by 7.38% and 1.4% respectively on the annotated corpus. Also we conduct experiments on COAE20081 public corpus to prove its generality. Finally this paper also offers a simple but efficient method to construct and perfect the collocation database for further use.