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 opinionelement 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.
opinion-sentiment relation extraction dependency parsing shallow semantic analysis ontology collocation
Chen Mosha Yao Tianfang
UDS-SJTU Joint Research Lab for Language Technology Dept. of Computer Science and Engineering Shanghai Jiaotong University, Shanghai 200240, China
国际会议
2010 4th International Universal Communication Symposium(第四届国际普遍交流学术研讨会 IUCS 2010)
北京
英文
298-304
2010-10-18（万方平台首次上网日期，不代表论文的发表时间）